feat: implement skills system for AI agents (#16865)
## Summary This PR introduces a Skills system for AI agents, inspired by the [Agent Skills specification](https://agentskills.io/specification). ## Changes ### Backend - **SkillEntity**: New database entity with migration for storing skills - **V2 Sync Mechanism**: Implemented FlatSkill, builders, validators, and action handlers following the v2 flat entity pattern - **Standard Skills**: Pre-defined skills (workflow-building, data-manipulation, dashboard-building, metadata-building, research, code-interpreter, xlsx, pdf, docx, pptx) - **GraphQL API**: CRUD operations for skills with proper guards and permissions - **Workspace Cache**: Integrated skills into the workspace cache system ### Frontend - **Skills Table**: Searchable table in AI settings showing all skills - **Skill Form**: Create/edit page with Label (primary), Description, and Content (markdown editor) - **API Name**: Following existing patterns, name is derived from label with advanced settings toggle for custom API names - **Standard vs Custom**: Standard skills are read-only, custom skills can be edited/deleted ## Key Design Decisions - Skills are stored in the database (Salesforce-like approach) rather than files - Name is derived from Label by default (isLabelSyncedWithName pattern) - Skills reference functions/files via @ mentions in markdown content rather than explicit relations - Standard skills are synced from code, custom skills are created via UI ## Screenshots Skills table and form UI follow existing settings patterns. ## Testing - [x] Lint passes - [x] Typecheck passes - [ ] CI tests
This commit is contained in:
Félix Malfait
@@ -1,6 +0,0 @@
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export type SkillDefinition = {
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name: string;
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label: string;
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description: string;
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content: string;
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};
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@@ -1,9 +0,0 @@
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import { Module } from '@nestjs/common';
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import { SkillsService } from './skills.service';
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@Module({
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providers: [SkillsService],
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exports: [SkillsService],
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})
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export class SkillsModule {}
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@@ -1,66 +0,0 @@
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import { Injectable } from '@nestjs/common';
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import { SkillDefinition } from 'src/engine/core-modules/skills/skill-definition.type';
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import { CODE_INTERPRETER_SKILL } from 'src/engine/core-modules/skills/skills/code-interpreter.skill';
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import { DASHBOARD_BUILDING_SKILL } from 'src/engine/core-modules/skills/skills/dashboard-building.skill';
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import { DATA_MANIPULATION_SKILL } from 'src/engine/core-modules/skills/skills/data-manipulation.skill';
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import { DOCX_SKILL } from 'src/engine/core-modules/skills/skills/docx.skill';
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import { METADATA_BUILDING_SKILL } from 'src/engine/core-modules/skills/skills/metadata-building.skill';
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import { PDF_SKILL } from 'src/engine/core-modules/skills/skills/pdf.skill';
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import { PPTX_SKILL } from 'src/engine/core-modules/skills/skills/pptx.skill';
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import { RESEARCH_SKILL } from 'src/engine/core-modules/skills/skills/research.skill';
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import { WORKFLOW_BUILDING_SKILL } from 'src/engine/core-modules/skills/skills/workflow-building.skill';
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import { XLSX_SKILL } from 'src/engine/core-modules/skills/skills/xlsx.skill';
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const SKILL_DEFINITIONS: SkillDefinition[] = [
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WORKFLOW_BUILDING_SKILL,
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DATA_MANIPULATION_SKILL,
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DASHBOARD_BUILDING_SKILL,
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METADATA_BUILDING_SKILL,
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RESEARCH_SKILL,
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CODE_INTERPRETER_SKILL,
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XLSX_SKILL,
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PDF_SKILL,
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DOCX_SKILL,
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PPTX_SKILL,
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];
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export type Skill = {
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name: string;
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label: string;
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description: string;
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content: string;
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};
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@Injectable()
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export class SkillsService {
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getAllSkills(): Skill[] {
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return SKILL_DEFINITIONS.map((skill) => ({
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name: skill.name,
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label: skill.label,
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description: skill.description,
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content: skill.content,
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}));
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}
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getSkillByName(name: string): Skill | undefined {
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const skillDef = SKILL_DEFINITIONS.find((skill) => skill.name === name);
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if (!skillDef) {
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return undefined;
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}
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return {
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name: skillDef.name,
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label: skillDef.label,
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description: skillDef.description,
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content: skillDef.content,
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};
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}
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getSkillsByNames(names: string[]): Skill[] {
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return names
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.map((name) => this.getSkillByName(name))
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.filter((skill): skill is Skill => skill !== undefined);
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}
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}
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-105
@@ -1,105 +0,0 @@
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import { type SkillDefinition } from 'src/engine/core-modules/skills/skill-definition.type';
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export const CODE_INTERPRETER_SKILL: SkillDefinition = {
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name: 'code-interpreter',
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label: 'Code Interpreter',
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description:
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'Python code execution for data analysis, complex multi-step operations, and efficient bulk processing via MCP bridge',
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content: `# Code Interpreter Skill
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You have access to the \`code_interpreter\` tool to execute Python code in a sandboxed environment.
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## How to Use
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Call the \`code_interpreter\` tool with your Python code. The tool will execute the code and return stdout, stderr, and any generated files.
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## Capabilities
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- Analyze CSV, Excel, and JSON data files
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- Create charts and visualizations (matplotlib, seaborn)
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- Generate reports (PDF, PPTX, Excel)
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- Perform calculations and data transformations
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## Pre-installed Libraries
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pandas, numpy, matplotlib, seaborn, scikit-learn, openpyxl, python-pptx
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## Input Files
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- User-uploaded files are available at \`/home/user/{filename}\`
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- Always check the file exists before processing
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## Output Files
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- Charts: Save to \`/home/user/output/\` directory - these are automatically returned as downloadable URLs
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- For matplotlib: \`plt.savefig('/home/user/output/chart.png')\`
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- Generated files: Save to \`/home/user/output/{filename}\`
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## Example: Create a Bar Chart
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\`\`\`python
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import matplotlib.pyplot as plt
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import os
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# Data
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months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun']
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sales = [100, 150, 200, 175, 250, 300]
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# Create chart
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plt.figure(figsize=(10, 6))
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plt.bar(months, sales, color='skyblue')
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plt.title('Monthly Sales')
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plt.xlabel('Month')
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plt.ylabel('Sales')
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plt.tight_layout()
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# Save to output directory
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os.makedirs('/home/user/output', exist_ok=True)
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plt.savefig('/home/user/output/sales_chart.png')
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print('Chart saved!')
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\`\`\`
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## Example: Analyze CSV
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\`\`\`python
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import pandas as pd
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import matplotlib.pyplot as plt
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import os
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# Load data
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df = pd.read_csv('/home/user/data.csv')
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print(f"Loaded {len(df)} rows")
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# Create visualization
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plt.figure(figsize=(10, 6))
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df.groupby('category')['value'].mean().plot(kind='bar')
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plt.title('Average Value by Category')
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plt.tight_layout()
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os.makedirs('/home/user/output', exist_ok=True)
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plt.savefig('/home/user/output/analysis.png')
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print('Analysis complete!')
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\`\`\`
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## Calling Twenty Tools from Python (MCP Bridge)
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A \`twenty\` helper is automatically available in your code. Use it to call any Twenty tool directly from Python:
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\`\`\`python
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# Find records
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people = twenty.call_tool('find_person_records', {'limit': 10})
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print(f"Found {len(people['edges'])} people")
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# Create a record
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result = twenty.call_tool('create_company_record', {
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'data': {'name': 'Acme Corp', 'domainName': {'primaryLinkUrl': 'acme.com'}}
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})
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print(f"Created company: {result['id']}")
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# Update a record
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twenty.call_tool('update_person_record', {
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'id': 'person-uuid',
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'data': {'jobTitle': 'CEO'}
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})
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# List available tools
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tools = twenty.list_tools()
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for tool in tools:
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print(f"- {tool['name']}: {tool['description']}")
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\`\`\`
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This allows you to orchestrate complex multi-step operations in a single code execution, which is more efficient than multiple tool calls.`,
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};
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-78
@@ -1,78 +0,0 @@
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import { type SkillDefinition } from 'src/engine/core-modules/skills/skill-definition.type';
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export const DASHBOARD_BUILDING_SKILL: SkillDefinition = {
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name: 'dashboard-building',
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label: 'Dashboard Building',
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description: 'Creating and managing dashboards with widgets and layouts',
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content: `# Dashboard Building Skill
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You help users create and manage dashboards with widgets.
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## CRITICAL: Creating GRAPH Widgets
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Before creating any GRAPH widget, you MUST:
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1. Use list_object_metadata_items to get the objectMetadataId (e.g., for "opportunity", "company")
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2. From the response, get the field IDs you need (aggregateFieldMetadataId, primaryAxisGroupByFieldMetadataId)
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GRAPH widgets require real UUIDs from the workspace metadata, NOT made-up values.
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## Widget Configuration
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### GRAPH - AGGREGATE (KPI numbers)
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Shows a single aggregated value (count, sum, average).
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Required:
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- objectMetadataId: UUID of the object (e.g., opportunity)
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- configuration.graphType: "AGGREGATE"
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- configuration.aggregateFieldMetadataId: UUID of field to aggregate
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- configuration.aggregateOperation: "COUNT", "SUM", "AVG", "MIN", "MAX"
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### GRAPH - BAR/LINE Charts
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Shows data grouped by a dimension.
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Required:
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- objectMetadataId: UUID of the object
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- configuration.graphType: "VERTICAL_BAR", "HORIZONTAL_BAR", or "LINE"
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- configuration.aggregateFieldMetadataId: field to aggregate
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- configuration.aggregateOperation: aggregation type
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- configuration.primaryAxisGroupByFieldMetadataId: field to group by (x-axis)
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### GRAPH - PIE Charts
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Shows data distribution as slices.
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Required:
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- objectMetadataId: UUID of the object
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- configuration.graphType: "PIE"
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- configuration.aggregateFieldMetadataId: field to aggregate
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- configuration.aggregateOperation: aggregation type
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- configuration.groupByFieldMetadataId: field to slice by
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### IFRAME
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Embeds external content:
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- configuration.url: "https://..."
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### STANDALONE_RICH_TEXT
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Text content widget:
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- configuration.body: "Your text here"
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## Grid System
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- 12 columns (0-11)
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- KPI widgets: rowSpan 2-4, columnSpan 3-4
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- Charts: rowSpan 6-8, columnSpan 6-12
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- Common layouts:
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- 4 KPIs in a row: each { columnSpan: 3 }
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- 2 charts side by side: each { columnSpan: 6 }
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- Full width chart: { column: 0, columnSpan: 12 }
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## Workflow
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1. Ask user what data they want to visualize
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2. Load list_object_metadata_items to discover available objects and fields
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3. Create dashboard with appropriate widgets using real field IDs
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4. Use get_dashboard to verify creation
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## Best Practices
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- Place KPIs at the top (row 0)
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- Group related charts together
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- Use consistent heights within rows
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- Start simple, add complexity as needed`,
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};
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-44
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import { type SkillDefinition } from 'src/engine/core-modules/skills/skill-definition.type';
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export const DATA_MANIPULATION_SKILL: SkillDefinition = {
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name: 'data-manipulation',
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label: 'Data Manipulation',
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description:
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'Searching, filtering, creating, and updating records across all objects',
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content: `# Data Manipulation Skill
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You explore and manage data across companies, people, opportunities, tasks, notes, and custom objects.
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## Capabilities
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- Search, filter, sort, create, update records
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- Manage relationships between records
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- Bulk operations and data analysis
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## Constraints
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- READ and WRITE access to all objects
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- CANNOT delete records or access workflow objects
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- CANNOT modify workspace settings
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## Multi-step Approach
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- Chain queries to solve complex requests (e.g., find companies → get their opportunities → calculate totals)
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- If a query fails or returns no results, try alternative filters or approaches
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- Validate data exists before referencing it (search before update)
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- Use results from one query to inform the next
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- Try 2-3 different approaches before giving up
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## Sorting (Critical)
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For "top N" queries, use orderBy with limit:
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- Examples: orderBy: [{"employees": "DescNullsLast"}], orderBy: [{"createdAt": "AscNullsFirst"}]
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- Valid directions: "AscNullsFirst", "AscNullsLast", "DescNullsFirst", "DescNullsLast"
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## Before Bulk Operations
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- Confirm the scope and impact
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- Explain what will change
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Prioritize data integrity and provide clear feedback on operations performed.`,
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};
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@@ -1,152 +0,0 @@
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import { type SkillDefinition } from 'src/engine/core-modules/skills/skill-definition.type';
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export const DOCX_SKILL: SkillDefinition = {
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name: 'docx',
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label: 'Word Documents',
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description:
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'Word document creation, editing, template processing, and OOXML manipulation',
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content: `# Word Document Processing Skill
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**IMPORTANT**: Save all output files to \`/home/user/output/\` for them to be downloadable.
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## Pre-installed Scripts (OOXML Editing)
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- \`python /home/user/scripts/docx/unpack.py <docx_file> <output_dir>\` - Unpack .docx to XML files for direct editing
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- \`python /home/user/scripts/docx/pack.py <input_dir> <docx_file>\` - Repack XML files into .docx
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- \`python /home/user/scripts/docx/validate.py <docx_file>\` - Validate document structure
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### Validation Scripts
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- \`/home/user/scripts/docx/validation/docx.py\` - DOCX validation module
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- \`/home/user/scripts/docx/validation/redlining.py\` - Track changes/redline validation
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## High-Level API (python-docx)
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### Reading Documents
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\`\`\`python
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from docx import Document
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doc = Document('document.docx')
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# Read paragraphs
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for para in doc.paragraphs:
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print(para.text)
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# Read tables
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for table in doc.tables:
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for row in table.rows:
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for cell in row.cells:
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print(cell.text)
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\`\`\`
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### Creating Documents
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\`\`\`python
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from docx import Document
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from docx.shared import Inches, Pt
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from docx.enum.text import WD_ALIGN_PARAGRAPH
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doc = Document()
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# Add heading
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doc.add_heading('Document Title', 0)
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# Add paragraph with formatting
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para = doc.add_paragraph('Normal text. ')
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run = para.add_run('Bold text.')
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run.bold = True
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# Add table
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table = doc.add_table(rows=2, cols=2)
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table.cell(0, 0).text = 'Header 1'
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table.cell(0, 1).text = 'Header 2'
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# Add image
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doc.add_picture('image.png', width=Inches(4))
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doc.save('/home/user/output/output.docx')
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\`\`\`
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## Low-Level OOXML Editing
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For complex edits (tracked changes, custom XML), use the unpack/edit/pack workflow:
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### Step 1: Unpack
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\`\`\`bash
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python /home/user/scripts/docx/unpack.py document.docx ./unpacked/
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\`\`\`
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### Step 2: Edit XML directly
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\`\`\`python
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import xml.etree.ElementTree as ET
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tree = ET.parse('./unpacked/word/document.xml')
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root = tree.getroot()
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# Edit XML...
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# Namespaces: w = http://schemas.openxmlformats.org/wordprocessingml/2006/main
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tree.write('./unpacked/word/document.xml', xml_declaration=True, encoding='UTF-8')
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\`\`\`
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### Step 3: Validate & Repack
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\`\`\`bash
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python /home/user/scripts/docx/validate.py ./unpacked/
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python /home/user/scripts/docx/pack.py ./unpacked/ /home/user/output/output.docx
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\`\`\`
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## Template Processing
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### Find and Replace
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\`\`\`python
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from docx import Document
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doc = Document('template.docx')
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|
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for para in doc.paragraphs:
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if '{{name}}' in para.text:
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para.text = para.text.replace('{{name}}', 'John Doe')
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doc.save('/home/user/output/filled.docx')
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\`\`\`
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### Preserve Formatting During Replace
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\`\`\`python
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def replace_in_paragraph(para, old_text, new_text):
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"""Replace text while preserving formatting"""
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for run in para.runs:
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if old_text in run.text:
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run.text = run.text.replace(old_text, new_text)
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|
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for para in doc.paragraphs:
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replace_in_paragraph(para, '{{name}}', 'John Doe')
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\`\`\`
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## Working with Styles
|
||||
|
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\`\`\`python
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from docx.shared import Pt, RGBColor
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|
||||
# Set font
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run.font.name = 'Arial'
|
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run.font.size = Pt(12)
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run.font.color.rgb = RGBColor(0, 0, 0)
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# Paragraph formatting
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para.alignment = WD_ALIGN_PARAGRAPH.CENTER
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para.paragraph_format.space_before = Pt(12)
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para.paragraph_format.space_after = Pt(12)
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\`\`\`
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||||
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## Quick Reference
|
||||
|
||||
| Task | Tool | Example |
|
||||
|------|------|---------|
|
||||
| Read document | python-docx | \`Document('file.docx')\` |
|
||||
| Create document | python-docx | \`Document()\` |
|
||||
| Add heading | python-docx | \`doc.add_heading('Title', 0)\` |
|
||||
| Add table | python-docx | \`doc.add_table(rows=2, cols=2)\` |
|
||||
| Unpack for editing | script | \`python unpack.py doc.docx ./out/\` |
|
||||
| Repack | script | \`python pack.py ./out/ doc.docx\` |
|
||||
| Validate | script | \`python validate.py doc.docx\` |`,
|
||||
};
|
||||
-64
@@ -1,64 +0,0 @@
|
||||
import { type SkillDefinition } from 'src/engine/core-modules/skills/skill-definition.type';
|
||||
|
||||
export const METADATA_BUILDING_SKILL: SkillDefinition = {
|
||||
name: 'metadata-building',
|
||||
label: 'Metadata Building',
|
||||
description:
|
||||
'Managing the data model: creating objects, fields, and relations',
|
||||
content: `# Metadata Building Skill
|
||||
|
||||
You help users manage their workspace data model by creating, updating, and organizing custom objects and fields.
|
||||
|
||||
## Capabilities
|
||||
|
||||
- Create new custom objects with appropriate naming and configuration
|
||||
- Add fields to existing objects (text, number, date, select, relation, etc.)
|
||||
- Update object and field properties (labels, descriptions, icons)
|
||||
- Manage field settings (required, unique, default values)
|
||||
- Create relations between objects
|
||||
|
||||
## Key Concepts
|
||||
|
||||
- **Objects**: Represent entities in the data model (e.g., Company, Person, Opportunity)
|
||||
- **Fields**: Properties of objects with specific types (TEXT, NUMBER, DATE_TIME, SELECT, RELATION, etc.)
|
||||
- **Relations**: Links between objects (one-to-many, many-to-one)
|
||||
- **Labels vs Names**: Labels are for display, names are internal identifiers (camelCase)
|
||||
|
||||
## Field Types Available
|
||||
|
||||
- **TEXT**: Simple text fields
|
||||
- **NUMBER**: Numeric values (integers or decimals)
|
||||
- **BOOLEAN**: True/false values
|
||||
- **DATE_TIME**: Date and time values
|
||||
- **DATE**: Date only values
|
||||
- **SELECT**: Single choice from options
|
||||
- **MULTI_SELECT**: Multiple choices from options
|
||||
- **LINK**: URL fields
|
||||
- **LINKS**: Multiple URL fields
|
||||
- **EMAIL**: Email address fields
|
||||
- **EMAILS**: Multiple email fields
|
||||
- **PHONE**: Phone number fields
|
||||
- **PHONES**: Multiple phone fields
|
||||
- **CURRENCY**: Monetary values
|
||||
- **RATING**: Star ratings
|
||||
- **RELATION**: Links to other objects
|
||||
- **RICH_TEXT**: Formatted text content
|
||||
|
||||
## Best Practices
|
||||
|
||||
- Use clear, descriptive names for objects and fields
|
||||
- Follow naming conventions: singular for object names, camelCase for field names
|
||||
- Add helpful descriptions to objects and fields
|
||||
- Choose appropriate field types for the data being stored
|
||||
- Consider relationships between objects when designing the data model
|
||||
|
||||
## Approach
|
||||
|
||||
- Ask clarifying questions to understand the user's data modeling needs
|
||||
- Suggest best practices for naming and organization
|
||||
- Explain the impact of changes to the data model
|
||||
- Verify object and field existence before making updates
|
||||
- Provide clear feedback on operations performed
|
||||
|
||||
Prioritize data model integrity and user understanding.`,
|
||||
};
|
||||
@@ -1,131 +0,0 @@
|
||||
import { type SkillDefinition } from 'src/engine/core-modules/skills/skill-definition.type';
|
||||
|
||||
export const PDF_SKILL: SkillDefinition = {
|
||||
name: 'pdf',
|
||||
label: 'PDF Processing',
|
||||
description:
|
||||
'PDF form filling, field extraction, table parsing, and validation',
|
||||
content: `# PDF Processing Skill
|
||||
|
||||
**IMPORTANT**: Save all output files to \`/home/user/output/\` for them to be downloadable.
|
||||
|
||||
## Pre-installed Scripts
|
||||
|
||||
### Field Extraction
|
||||
- \`python /home/user/scripts/pdf/extract_form_field_info.py <pdf_file>\` - Extract all fillable field names and types (JSON output)
|
||||
- \`python /home/user/scripts/pdf/check_fillable_fields.py <pdf_file>\` - Check if PDF has fillable fields
|
||||
|
||||
### Form Filling
|
||||
- \`python /home/user/scripts/pdf/fill_fillable_fields.py <pdf_file> <json_data> <output_file>\` - Fill PDF form fields
|
||||
- \`python /home/user/scripts/pdf/fill_pdf_form_with_annotations.py <pdf_file> <json_data> <output_file>\` - Fill with annotation support
|
||||
|
||||
### Validation
|
||||
- \`python /home/user/scripts/pdf/create_validation_image.py <pdf_file>\` - Create validation image of filled PDF
|
||||
- \`python /home/user/scripts/pdf/check_bounding_boxes.py <pdf_file>\` - Check field boundaries
|
||||
- \`python /home/user/scripts/pdf/convert_pdf_to_images.py <pdf_file>\` - Convert PDF pages to images
|
||||
|
||||
## Reading PDFs
|
||||
|
||||
\`\`\`python
|
||||
import fitz # PyMuPDF
|
||||
|
||||
# Open PDF
|
||||
doc = fitz.open('document.pdf')
|
||||
|
||||
# Extract text from all pages
|
||||
for page in doc:
|
||||
text = page.get_text()
|
||||
print(text)
|
||||
|
||||
# Extract text from specific page
|
||||
page = doc[0] # First page
|
||||
text = page.get_text()
|
||||
\`\`\`
|
||||
|
||||
## Extracting Tables
|
||||
|
||||
\`\`\`python
|
||||
import pdfplumber
|
||||
|
||||
with pdfplumber.open('document.pdf') as pdf:
|
||||
for page in pdf.pages:
|
||||
tables = page.extract_tables()
|
||||
for table in tables:
|
||||
for row in table:
|
||||
print(row)
|
||||
\`\`\`
|
||||
|
||||
## Filling PDF Forms
|
||||
|
||||
### Step 1: Extract field information
|
||||
\`\`\`bash
|
||||
python /home/user/scripts/pdf/extract_form_field_info.py form.pdf > fields.json
|
||||
\`\`\`
|
||||
|
||||
### Step 2: Create fill data JSON
|
||||
\`\`\`json
|
||||
{
|
||||
"field_name_1": "value1",
|
||||
"field_name_2": "value2",
|
||||
"checkbox_field": true
|
||||
}
|
||||
\`\`\`
|
||||
|
||||
### Step 3: Fill the form
|
||||
\`\`\`bash
|
||||
python /home/user/scripts/pdf/fill_fillable_fields.py form.pdf fill_data.json /home/user/output/output.pdf
|
||||
\`\`\`
|
||||
|
||||
### Step 4: Validate the output
|
||||
\`\`\`bash
|
||||
python /home/user/scripts/pdf/create_validation_image.py /home/user/output/output.pdf
|
||||
\`\`\`
|
||||
|
||||
## Creating PDFs
|
||||
|
||||
\`\`\`python
|
||||
from reportlab.lib.pagesizes import letter
|
||||
from reportlab.pdfgen import canvas
|
||||
|
||||
c = canvas.Canvas('/home/user/output/output.pdf', pagesize=letter)
|
||||
c.drawString(100, 750, 'Hello World!')
|
||||
c.save()
|
||||
\`\`\`
|
||||
|
||||
## Merging PDFs
|
||||
|
||||
\`\`\`python
|
||||
from PyPDF2 import PdfMerger
|
||||
|
||||
merger = PdfMerger()
|
||||
merger.append('file1.pdf')
|
||||
merger.append('file2.pdf')
|
||||
merger.write('/home/user/output/merged.pdf')
|
||||
merger.close()
|
||||
\`\`\`
|
||||
|
||||
## Splitting PDFs
|
||||
|
||||
\`\`\`python
|
||||
from PyPDF2 import PdfReader, PdfWriter
|
||||
|
||||
reader = PdfReader('document.pdf')
|
||||
|
||||
# Extract specific pages
|
||||
writer = PdfWriter()
|
||||
writer.add_page(reader.pages[0]) # First page
|
||||
writer.write('/home/user/output/page1.pdf')
|
||||
\`\`\`
|
||||
|
||||
## Quick Reference
|
||||
|
||||
| Task | Tool | Command/Example |
|
||||
|------|------|-----------------|
|
||||
| Extract text | PyMuPDF | \`page.get_text()\` |
|
||||
| Extract tables | pdfplumber | \`page.extract_tables()\` |
|
||||
| List form fields | script | \`python extract_form_field_info.py form.pdf\` |
|
||||
| Fill form | script | \`python fill_fillable_fields.py form.pdf data.json out.pdf\` |
|
||||
| Validate fill | script | \`python create_validation_image.py filled.pdf\` |
|
||||
| Create PDF | reportlab | \`canvas.Canvas('out.pdf')\` |
|
||||
| Merge PDFs | PyPDF2 | \`PdfMerger()\` |`,
|
||||
};
|
||||
@@ -1,170 +0,0 @@
|
||||
import { type SkillDefinition } from 'src/engine/core-modules/skills/skill-definition.type';
|
||||
|
||||
export const PPTX_SKILL: SkillDefinition = {
|
||||
name: 'pptx',
|
||||
label: 'PowerPoint',
|
||||
description:
|
||||
'PowerPoint creation, editing, templates, thumbnails, and slide manipulation',
|
||||
content: `# PowerPoint Processing Skill
|
||||
|
||||
**IMPORTANT**: Save all output files to \`/home/user/output/\` for them to be downloadable.
|
||||
|
||||
## Pre-installed Scripts
|
||||
|
||||
- \`python /home/user/scripts/pptx/thumbnail.py <pptx_file> [output_dir]\` - Generate slide thumbnails
|
||||
- \`python /home/user/scripts/pptx/rearrange.py <pptx_file> <slide_order_json> <output_file>\` - Reorder slides
|
||||
- \`python /home/user/scripts/pptx/inventory.py <pptx_file>\` - List all slides and their content
|
||||
- \`python /home/user/scripts/pptx/replace.py <pptx_file> <replacements_json> <output_file>\` - Find/replace text
|
||||
|
||||
## Reading Presentations
|
||||
|
||||
\`\`\`python
|
||||
from pptx import Presentation
|
||||
|
||||
prs = Presentation('presentation.pptx')
|
||||
|
||||
# Iterate through slides
|
||||
for slide in prs.slides:
|
||||
for shape in slide.shapes:
|
||||
if shape.has_text_frame:
|
||||
print(shape.text)
|
||||
\`\`\`
|
||||
|
||||
## Creating Presentations
|
||||
|
||||
\`\`\`python
|
||||
from pptx import Presentation
|
||||
from pptx.util import Inches, Pt
|
||||
|
||||
prs = Presentation()
|
||||
|
||||
# Add title slide
|
||||
slide_layout = prs.slide_layouts[0] # Title layout
|
||||
slide = prs.slides.add_slide(slide_layout)
|
||||
title = slide.shapes.title
|
||||
subtitle = slide.placeholders[1]
|
||||
|
||||
title.text = "Presentation Title"
|
||||
subtitle.text = "Subtitle goes here"
|
||||
|
||||
# Add content slide
|
||||
slide_layout = prs.slide_layouts[1] # Title and content
|
||||
slide = prs.slides.add_slide(slide_layout)
|
||||
title = slide.shapes.title
|
||||
body = slide.placeholders[1]
|
||||
|
||||
title.text = "Slide Title"
|
||||
tf = body.text_frame
|
||||
tf.text = "First bullet"
|
||||
p = tf.add_paragraph()
|
||||
p.text = "Second bullet"
|
||||
p.level = 1
|
||||
|
||||
prs.save('/home/user/output/output.pptx')
|
||||
\`\`\`
|
||||
|
||||
## Adding Images
|
||||
|
||||
\`\`\`python
|
||||
from pptx.util import Inches
|
||||
|
||||
slide = prs.slides.add_slide(prs.slide_layouts[6]) # Blank layout
|
||||
slide.shapes.add_picture(
|
||||
'image.png',
|
||||
left=Inches(1),
|
||||
top=Inches(1),
|
||||
width=Inches(5)
|
||||
)
|
||||
\`\`\`
|
||||
|
||||
## Adding Tables
|
||||
|
||||
\`\`\`python
|
||||
from pptx.util import Inches
|
||||
|
||||
slide = prs.slides.add_slide(prs.slide_layouts[6])
|
||||
table = slide.shapes.add_table(
|
||||
rows=3, cols=3,
|
||||
left=Inches(1), top=Inches(1),
|
||||
width=Inches(8), height=Inches(2)
|
||||
).table
|
||||
|
||||
# Set cell values
|
||||
table.cell(0, 0).text = "Header 1"
|
||||
table.cell(0, 1).text = "Header 2"
|
||||
table.cell(1, 0).text = "Data 1"
|
||||
\`\`\`
|
||||
|
||||
## Adding Charts
|
||||
|
||||
\`\`\`python
|
||||
from pptx.chart.data import CategoryChartData
|
||||
from pptx.enum.chart import XL_CHART_TYPE
|
||||
from pptx.util import Inches
|
||||
|
||||
chart_data = CategoryChartData()
|
||||
chart_data.categories = ['East', 'West', 'Midwest']
|
||||
chart_data.add_series('Series 1', (19.2, 21.4, 16.7))
|
||||
|
||||
slide = prs.slides.add_slide(prs.slide_layouts[6])
|
||||
chart = slide.shapes.add_chart(
|
||||
XL_CHART_TYPE.COLUMN_CLUSTERED,
|
||||
Inches(1), Inches(1), Inches(8), Inches(5),
|
||||
chart_data
|
||||
).chart
|
||||
\`\`\`
|
||||
|
||||
## Using Scripts
|
||||
|
||||
### Generate Thumbnails
|
||||
\`\`\`bash
|
||||
python /home/user/scripts/pptx/thumbnail.py presentation.pptx ./thumbnails/
|
||||
# Creates: thumbnails/slide_1.png, slide_2.png, etc.
|
||||
\`\`\`
|
||||
|
||||
### Get Slide Inventory
|
||||
\`\`\`bash
|
||||
python /home/user/scripts/pptx/inventory.py presentation.pptx
|
||||
# Returns JSON with all slide content and shapes
|
||||
\`\`\`
|
||||
|
||||
### Reorder Slides
|
||||
\`\`\`bash
|
||||
# Order: [3, 1, 2] means slide 3 becomes first, slide 1 second, etc.
|
||||
python /home/user/scripts/pptx/rearrange.py input.pptx '[3, 1, 2]' output.pptx
|
||||
\`\`\`
|
||||
|
||||
### Find and Replace Text
|
||||
\`\`\`bash
|
||||
python /home/user/scripts/pptx/replace.py input.pptx '{"{{company}}": "Acme Corp", "{{date}}": "2024"}' output.pptx
|
||||
\`\`\`
|
||||
|
||||
## Template Processing Workflow
|
||||
|
||||
1. **Generate thumbnails** to understand slide structure:
|
||||
\`\`\`bash
|
||||
python /home/user/scripts/pptx/thumbnail.py template.pptx ./preview/
|
||||
\`\`\`
|
||||
|
||||
2. **Get inventory** to find placeholder text:
|
||||
\`\`\`bash
|
||||
python /home/user/scripts/pptx/inventory.py template.pptx
|
||||
\`\`\`
|
||||
|
||||
3. **Replace placeholders**:
|
||||
\`\`\`bash
|
||||
python /home/user/scripts/pptx/replace.py template.pptx '{"{{title}}": "Q4 Report"}' output.pptx
|
||||
\`\`\`
|
||||
|
||||
## Quick Reference
|
||||
|
||||
| Task | Tool | Example |
|
||||
|------|------|---------|
|
||||
| Read presentation | python-pptx | \`Presentation('file.pptx')\` |
|
||||
| Create presentation | python-pptx | \`Presentation()\` |
|
||||
| Add slide | python-pptx | \`prs.slides.add_slide(layout)\` |
|
||||
| Generate thumbnails | script | \`python thumbnail.py pres.pptx ./out/\` |
|
||||
| Get slide inventory | script | \`python inventory.py pres.pptx\` |
|
||||
| Reorder slides | script | \`python rearrange.py pres.pptx '[2,1,3]' out.pptx\` |
|
||||
| Find/replace | script | \`python replace.py pres.pptx '{...}' out.pptx\` |`,
|
||||
};
|
||||
@@ -1,34 +0,0 @@
|
||||
import { type SkillDefinition } from 'src/engine/core-modules/skills/skill-definition.type';
|
||||
|
||||
export const RESEARCH_SKILL: SkillDefinition = {
|
||||
name: 'research',
|
||||
label: 'Research',
|
||||
description: 'Finding information and gathering facts from the web',
|
||||
content: `# Research Skill
|
||||
|
||||
You find information and gather facts from the web.
|
||||
|
||||
## Capabilities
|
||||
|
||||
- Search for current information and facts
|
||||
- Research companies, people, technologies, trends
|
||||
- Gather competitive intelligence and market data
|
||||
- Find contact details and verify information
|
||||
|
||||
## Research Strategy
|
||||
|
||||
- Try multiple search queries from different angles
|
||||
- If initial searches fail, use alternative search terms
|
||||
- Cross-reference information when possible
|
||||
- Cite sources and provide context
|
||||
|
||||
## Present Findings
|
||||
|
||||
- Be thorough but concise
|
||||
- Organize information logically
|
||||
- Distinguish facts from speculation
|
||||
- Note if information might be outdated
|
||||
- Include relevant sources
|
||||
|
||||
Be persistent in finding accurate information.`,
|
||||
};
|
||||
-62
@@ -1,62 +0,0 @@
|
||||
import { type SkillDefinition } from 'src/engine/core-modules/skills/skill-definition.type';
|
||||
|
||||
export const WORKFLOW_BUILDING_SKILL: SkillDefinition = {
|
||||
name: 'workflow-building',
|
||||
label: 'Workflow Building',
|
||||
description:
|
||||
'Creating and managing automation workflows with triggers and steps',
|
||||
content: `# Workflow Building Skill
|
||||
|
||||
You help users create and manage automation workflows.
|
||||
|
||||
## Capabilities
|
||||
|
||||
- Create workflows from scratch
|
||||
- Modify existing workflows (add, remove, update steps)
|
||||
- Explain workflow structure and suggest improvements
|
||||
|
||||
## Key Concepts
|
||||
|
||||
- **Triggers**: DATABASE_EVENT, MANUAL, CRON, WEBHOOK
|
||||
- **Steps**: CREATE_RECORD, SEND_EMAIL, CODE, etc.
|
||||
- **Data flow**: Use {{stepId.fieldName}} to reference previous step outputs
|
||||
- **Relationships**: Use nested objects like {"company": {"id": "{{reference}}"}}
|
||||
|
||||
## CRON Trigger Settings Schema
|
||||
|
||||
For CRON triggers, settings.type must be one of these exact values:
|
||||
|
||||
1. **DAYS** - Daily schedule
|
||||
- Requires: schedule: { day: number (1+), hour: number (0-23), minute: number (0-59) }
|
||||
- Example: { type: "DAYS", schedule: { day: 1, hour: 9, minute: 0 }, outputSchema: {} }
|
||||
|
||||
2. **HOURS** - Hourly schedule (USE THIS FOR "EVERY HOUR")
|
||||
- Requires: schedule: { hour: number (1+), minute: number (0-59) }
|
||||
- Example: { type: "HOURS", schedule: { hour: 1, minute: 0 }, outputSchema: {} }
|
||||
- This runs every X hours at Y minutes past the hour
|
||||
|
||||
3. **MINUTES** - Minute-based schedule
|
||||
- Requires: schedule: { minute: number (1+) }
|
||||
- Example: { type: "MINUTES", schedule: { minute: 15 }, outputSchema: {} }
|
||||
|
||||
4. **CUSTOM** - Custom cron pattern
|
||||
- Requires: pattern: string (cron expression)
|
||||
- Example: { type: "CUSTOM", pattern: "0 * * * *", outputSchema: {} }
|
||||
|
||||
## Critical Notes
|
||||
|
||||
Always rely on tool schema definitions:
|
||||
- The workflow creation tool provides comprehensive schemas with examples
|
||||
- Follow schema definitions exactly for field names, types, and structures
|
||||
- Schema includes validation rules and common patterns
|
||||
|
||||
## Approach
|
||||
|
||||
- Ask clarifying questions to understand user needs
|
||||
- Suggest appropriate actions for the use case
|
||||
- Explain each step and why it's needed
|
||||
- For modifications, understand current structure first
|
||||
- Ensure workflow logic remains coherent
|
||||
|
||||
Prioritize user understanding and workflow effectiveness.`,
|
||||
};
|
||||
@@ -1,131 +0,0 @@
|
||||
import { type SkillDefinition } from 'src/engine/core-modules/skills/skill-definition.type';
|
||||
|
||||
export const XLSX_SKILL: SkillDefinition = {
|
||||
name: 'xlsx',
|
||||
label: 'Excel & Spreadsheets',
|
||||
description:
|
||||
'Excel/spreadsheet creation, editing, and analysis with formulas, formatting, and visualization',
|
||||
content: `# Excel Processing Skill
|
||||
|
||||
**IMPORTANT**: Save all output files to \`/home/user/output/\` for them to be downloadable.
|
||||
|
||||
## Pre-installed Scripts
|
||||
|
||||
- \`python /home/user/scripts/xlsx/recalc.py <excel_file> [timeout]\` - Recalculate formulas using LibreOffice
|
||||
|
||||
## Requirements
|
||||
|
||||
### Zero Formula Errors
|
||||
Every Excel model MUST be delivered with ZERO formula errors (#REF!, #DIV/0!, #VALUE!, #N/A, #NAME?)
|
||||
|
||||
### Use Formulas, Not Hardcoded Values
|
||||
**Always use Excel formulas instead of calculating values in Python and hardcoding them.**
|
||||
|
||||
\`\`\`python
|
||||
# ❌ WRONG - Hardcoding
|
||||
total = df['Sales'].sum()
|
||||
sheet['B10'] = total
|
||||
|
||||
# ✅ CORRECT - Using formulas
|
||||
sheet['B10'] = '=SUM(B2:B9)'
|
||||
\`\`\`
|
||||
|
||||
## Reading and Analyzing Data
|
||||
|
||||
\`\`\`python
|
||||
import pandas as pd
|
||||
|
||||
# Read Excel
|
||||
df = pd.read_excel('file.xlsx')
|
||||
all_sheets = pd.read_excel('file.xlsx', sheet_name=None) # All sheets as dict
|
||||
|
||||
# Analyze
|
||||
df.head()
|
||||
df.info()
|
||||
df.describe()
|
||||
\`\`\`
|
||||
|
||||
## Creating New Excel Files
|
||||
|
||||
\`\`\`python
|
||||
from openpyxl import Workbook
|
||||
from openpyxl.styles import Font, PatternFill, Alignment
|
||||
|
||||
wb = Workbook()
|
||||
sheet = wb.active
|
||||
|
||||
# Add data
|
||||
sheet['A1'] = 'Hello'
|
||||
sheet.append(['Row', 'of', 'data'])
|
||||
|
||||
# Add formula
|
||||
sheet['B2'] = '=SUM(A1:A10)'
|
||||
|
||||
# Formatting
|
||||
sheet['A1'].font = Font(bold=True)
|
||||
sheet['A1'].fill = PatternFill('solid', start_color='FFFF00')
|
||||
sheet['A1'].alignment = Alignment(horizontal='center')
|
||||
|
||||
# Column width
|
||||
sheet.column_dimensions['A'].width = 20
|
||||
|
||||
wb.save('/home/user/output/output.xlsx')
|
||||
\`\`\`
|
||||
|
||||
## Editing Existing Files
|
||||
|
||||
\`\`\`python
|
||||
from openpyxl import load_workbook
|
||||
|
||||
wb = load_workbook('existing.xlsx')
|
||||
sheet = wb.active
|
||||
|
||||
# Modify cells
|
||||
sheet['A1'] = 'New Value'
|
||||
sheet.insert_rows(2)
|
||||
|
||||
wb.save('/home/user/output/modified.xlsx')
|
||||
\`\`\`
|
||||
|
||||
## Recalculating Formulas (MANDATORY)
|
||||
|
||||
After creating/editing files with formulas, run:
|
||||
\`\`\`bash
|
||||
python /home/user/scripts/xlsx/recalc.py /home/user/output/output.xlsx
|
||||
\`\`\`
|
||||
|
||||
The script returns JSON with error details:
|
||||
\`\`\`json
|
||||
{
|
||||
"status": "success",
|
||||
"total_errors": 0,
|
||||
"total_formulas": 42,
|
||||
"error_summary": {}
|
||||
}
|
||||
\`\`\`
|
||||
|
||||
If errors found, fix them and recalculate again.
|
||||
|
||||
## Financial Model Color Coding
|
||||
|
||||
- **Blue text**: Hardcoded inputs
|
||||
- **Black text**: Formulas and calculations
|
||||
- **Green text**: Links from other worksheets
|
||||
- **Yellow background**: Key assumptions needing attention
|
||||
|
||||
## Number Formatting
|
||||
|
||||
- Years: Format as text ("2024" not "2,024")
|
||||
- Currency: Use $#,##0 format
|
||||
- Percentages: 0.0% format
|
||||
- Negatives: Use parentheses (123) not minus -123
|
||||
|
||||
## Quick Reference
|
||||
|
||||
| Task | Tool | Example |
|
||||
|------|------|---------|
|
||||
| Read Excel | pandas | \`pd.read_excel('file.xlsx')\` |
|
||||
| Create Excel | openpyxl | \`Workbook()\` |
|
||||
| Add formula | openpyxl | \`sheet['B2'] = '=SUM(A1:A10)'\` |
|
||||
| Recalculate | script | \`python /home/user/scripts/xlsx/recalc.py file.xlsx\` |`,
|
||||
};
|
||||
+3
-3
@@ -1,6 +1,6 @@
|
||||
import { z } from 'zod';
|
||||
|
||||
import { type Skill } from 'src/engine/core-modules/skills/skills.service';
|
||||
import { type FlatSkill } from 'src/engine/metadata-modules/flat-skill/types/flat-skill.type';
|
||||
|
||||
export const LOAD_SKILL_TOOL_NAME = 'load_skill';
|
||||
|
||||
@@ -25,7 +25,7 @@ export type LoadSkillResult = {
|
||||
message: string;
|
||||
};
|
||||
|
||||
export type LoadSkillFunction = (names: string[]) => Skill[];
|
||||
export type LoadSkillFunction = (names: string[]) => Promise<FlatSkill[]>;
|
||||
|
||||
export const createLoadSkillTool = (loadSkills: LoadSkillFunction) => ({
|
||||
description:
|
||||
@@ -36,7 +36,7 @@ export const createLoadSkillTool = (loadSkills: LoadSkillFunction) => ({
|
||||
}): Promise<LoadSkillResult> => {
|
||||
const { skillNames } = parameters.input;
|
||||
|
||||
const skills = loadSkills(skillNames);
|
||||
const skills = await loadSkills(skillNames);
|
||||
|
||||
if (skills.length === 0) {
|
||||
return {
|
||||
|
||||
Reference in New Issue
Block a user