skill-template-generator
- Repo stars 6,311
- Author updated Live
- Author repo OpenSpace
- Domain
- Data
- Compatible agents
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- Claude Code
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- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @HKUDS · no license declared
- Token usage
- Lean
- Setup complexity
- Guided setup
- External API key
- Required · Vendor-specific
- Operating systems
- Unspecified (assume cross-platform)
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Shell exec
- Network behavior
- External requests
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: skill-template-generator
description: Generate properly-formatted SKILL.md files from extracted architectural patterns. Turns raw patt…
category: data
runtime: no special runtime
---
# skill-template-generator output preview
## PART A: Task fit
- Use case: Generate properly-formatted SKILL.md files from extracted architectural patterns. Turns raw pattern descriptions into reusable skills that OpenSpace can discover, select, and evolve..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “When to Use / SKILL.md Format / Frontmatter (Required)” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Generate properly-formatted SKILL.md files from extracted architectural patterns. Turns raw pattern descriptions into reusable skills that OpenSpace can discover, select, and evolve.”.
- **02** When the source has headings, the agent prioritizes “When to Use / SKILL.md Format / Frontmatter (Required)” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files, run shell commands; may access external network resources; requires Vendor-specific API keys.
## Running Rules
- read files, write/modify files, run shell commands; may access external network resources; requires Vendor-specific API keys.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files, run shell commands.
Start with a small task and check whether the result follows “When to Use / SKILL.md Format / Frontmatter (Required)”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: skill-template-generator
description: Generate properly-formatted SKILL.md files from extracted architectural patterns. Turns raw patt…
category: data
source: HKUDS/OpenSpace
---
# skill-template-generator
## When to use
- Generate properly-formatted SKILL.md files from extracted architectural patterns. Turns raw pattern descriptions into…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “When to Use / SKILL.md Format / Frontmatter (Required)” and keep inference separate from source facts.
- read files, write/modify files, run shell commands; may access external network resources; requires Vendor-specific API keys.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "skill-template-generator" {
input -> user goal + target files + boundaries + acceptance criteria
context -> When to Use / SKILL.md Format / Frontmatter (Required)
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files, run shell commands | may access external network resources
guardrails -> requires Vendor-specific API keys + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} Skill Template Generator
Given a structured pattern description (from codebase-pattern-analyzer or manual analysis), generate a valid SKILL.md file that OpenSpace can register, select for tasks, and evolve over time.
When to Use
- After extracting a pattern from a reference codebase, you need to package it as a reusable skill
- You want to create a new skill that teaches an agent how to perform a specific kind of task
- You are converting informal documentation or code examples into the SKILL.md format
SKILL.md Format
Every skill is a directory containing at minimum a SKILL.md file:
my-skill-name/
├── SKILL.md # Required — the skill definition
├── scripts/ # Optional — helper scripts
├── references/ # Optional — reference data files
└── assets/ # Optional — images, templates
Frontmatter (Required)
The file MUST start with YAML frontmatter containing exactly two fields:
---
name: my-skill-name
description: One-sentence description of what this skill teaches. Must be specific enough for LLM skill selection to match it to relevant tasks.
---
Rules:
namemust match the directory name (kebab-case, lowercase)descriptionshould be 15-40 words, include key terms an LLM would search for- No other frontmatter fields — everything else goes in the markdown body
Body Structure
The markdown body follows this template:
# [Skill Title]
[1-2 sentence summary of what this skill enables]
## When to Use
- [Trigger condition 1]
- [Trigger condition 2]
- [Trigger condition 3]
## [Core Content Sections]
[Step-by-step instructions, code templates, API references, etc.]
## Key Patterns
1. [Convention or best practice 1]
2. [Convention or best practice 2]
...
Step 1: Determine Skill Category
Match the pattern to one of three OpenSpace categories:
| Category | Use When | Example |
|---|---|---|
tool_guide |
The skill teaches how to use a specific tool or technique | "How to analyze a codebase", "How to use Finnhub API" |
workflow |
The skill prescribes an end-to-end procedure with ordered steps | "Create a panel component", "Set up API proxy endpoint" |
reference |
The skill provides knowledge that informs decisions | "WorldMonitor architecture index", "News API comparison" |
The category affects how OpenSpace judges the skill during execution analysis:
- workflow: Was the agent able to follow the prescribed steps?
- tool_guide: Did the agent use the described tool/approach?
- reference: Did the knowledge influence agent decisions?
Step 2: Write the Description
The description field is the most critical line — it determines whether OpenSpace selects this skill for a given task.
Good descriptions (specific, searchable):
- "Create a dashboard panel component using vanilla TypeScript DOM API, following the worldmonitor Panel architecture."
- "Integrate with Finnhub Stock API for real-time and historical stock market data."
- "CSS grid layout system for a responsive panel dashboard with dark theme."
Bad descriptions (vague, generic):
- "A useful skill for building things."
- "TypeScript patterns."
- "How to make a panel."
Formula: [Action verb] + [specific subject] + [key technology/approach] + [context/project reference]
Step 3: Write Actionable Instructions
The body must be concrete enough that an AI agent can follow it without guessing.
For Workflow Skills
Include:
- File paths — exact paths where files should be created (
src/components/MyPanel.ts) - Code templates — complete, runnable code blocks (not pseudocode)
- Import statements — every import the code needs
- Interface definitions — typed data shapes
- Integration points — how this connects to other parts of the project
Use {baseDir} for paths relative to the skill directory:
Read the reference file at {baseDir}/references/example.json
For Tool Guide Skills
Include:
- API endpoints — full URLs with parameter documentation
- Auth mechanism — how to authenticate (query param, header, etc.)
- Response shapes — JSON examples with field descriptions
- Rate limits — free tier limitations
- Error handling — common errors and how to handle them
For Reference Skills
Include:
- Structured index — tables, lists, or maps of the reference material
- Key file paths — where to find specific things in the reference codebase
- Architecture decisions — WHY certain patterns were chosen
- Comparison tables — alternatives and tradeoffs
Step 4: Add Dependency Hints
If the skill depends on patterns from other skills, mention them explicitly:
## Prerequisites
This skill builds on:
- `panel-component` — for the Panel base class
- `data-service` — for the circuit breaker pattern
- `api-proxy-endpoint` — for server-side API key isolation
This helps OpenSpace understand skill composition when DERIVING new skills.
Step 5: Validate the Skill
Before saving, verify:
- Frontmatter is valid YAML — no tabs, proper indentation, quotes around special chars
- Name matches directory —
name: foo-barlives infoo-bar/SKILL.md - Code blocks are complete — every snippet can be copy-pasted and run
- No broken references — all file paths and URLs are valid
- Description is specific — would an LLM pick this skill for the right task?
Example: Converting a Pattern to a Skill
Input (from codebase-pattern-analyzer):
Pattern: Circuit Breaker Data Service
Source: worldmonitor/src/services/*.ts
Category: service
Structure: Module-level CircuitBreaker instance, async fetch functions, typed interfaces
Key code: createCircuitBreaker({ name, cacheTtlMs }), breaker.execute(fn, default)
Output (data-service/SKILL.md):
---
name: data-service
description: Create data fetching services with circuit breaker pattern for API resilience. Services handle fetch, cache, retry, and expose typed data to panel components.
---
# Data Service Pattern
Each panel's data comes from a dedicated service module in `src/services/`. ...
## Circuit Breaker
[Full implementation code]
## Service Module Pattern
[Template with typed interfaces, breaker usage, export functions]
## Key Patterns
1. One circuit breaker per API endpoint
2. Export typed interfaces for data shapes
3. Wrap fetch calls in breaker.execute(fn, defaultValue)
...
Evolution Hooks
Skills generated by this workflow are designed to evolve:
- FIX: When an API changes or code pattern breaks, OpenSpace updates the skill in-place
- DERIVED: When a new panel needs a similar service, OpenSpace derives a specialized version
- CAPTURED: When an agent discovers a novel pattern during execution, OpenSpace captures it as a new skill
The better the initial skill quality, the better the evolved descendants.
Decide Fit First
Design Intent
How To Use It
Boundaries And Review