skill-python-implementation

Implement Python code. Invoke for Python-language implementation tasks.

438 stars

Best use case

skill-python-implementation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Implement Python code. Invoke for Python-language implementation tasks.

Teams using skill-python-implementation should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/skill-python-implementation/SKILL.md --create-dirs "https://raw.githubusercontent.com/benbrastmckie/nvim/main/.claude/extensions/python/skills/skill-python-implementation/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/skill-python-implementation/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How skill-python-implementation Compares

Feature / Agentskill-python-implementationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Implement Python code. Invoke for Python-language implementation tasks.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Python Implementation Skill

Thin wrapper that delegates Python implementation to `python-implementation-agent` subagent.

## Trigger Conditions

This skill activates when:
- Task language is "python"
- /implement command targets a Python task
- Plan exists and task is ready for implementation

## Execution Flow

### Stage 1: Input Validation
Validate task_number exists and language is "python".

### Stage 2: Preflight Status Update
Update status to "implementing" BEFORE invoking subagent.

### Stage 3: Prepare Delegation Context
Include task_context, plan_path, metadata_file_path.

### Stage 4: Invoke Subagent
Use Task tool with subagent_type: "python-implementation-agent".

### Stage 5: Parse Subagent Return
Read metadata from `specs/{N}_{SLUG}/.return-meta.json`.

### Stage 6: Update Task Status (Postflight)
Update state.json and TODO.md based on result.

### Stage 7: Link Artifacts
Add artifact to state.json with summary.

### Stage 8: Git Commit
Commit changes with session ID.

### Stage 9: Return Brief Summary

## MUST NOT (Postflight Boundary)

After the agent returns, this skill MUST NOT:

1. **Edit .py files** - All Python work is done by agent
2. **Run pytest/python** - Testing is done by agent
3. **Analyze or grep source** - Analysis is agent work
4. **Write summary/reports** - Artifact creation is agent work

The postflight phase is LIMITED TO:
- Reading agent metadata file
- Updating state.json via jq
- Updating TODO.md status marker via Edit
- Linking artifacts in state.json
- Git commit
- Cleanup of temp/marker files

Reference: @.claude/context/standards/postflight-tool-restrictions.md

---

## Return Format

Brief text summary (NOT JSON).

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