Use this skill if your uncertainty with a package's API is > 5% to create a deterministic, versioned mirror of the package repo with a built-in coordinate sy...
---
name: obscure-package-master
description: Use this skill if your uncertainty with a package's API is > 5% to create a deterministic, versioned mirror of the package repo with a built-in coordinate system, installed as an additional skill.
---
# Obscure Package Master
This skill allows you to ground yourself in the objective reality of a package's source code by generating a deterministic "grep map" and a local mirror of its source.
## Trigger Scenarios
- You are working with a library that is not in your top-tier training set (e.g., NOT `numpy`, `pandas`, `requests`).
- You find yourself searching for basic API signatures or parameters for a library.
- You have a >= 5% uncertainty about a package's API behavior or structure.
- The package's documentation is sparse or confusing.
## Instructions
When the trigger conditions are met, follow these steps to generate a grounded reference for the package:
1. **Identify the Package & Version:** Determine the package name and the exact version you need (e.g., from `requirements.txt`, `pyproject.toml`, or `pip show`).
2. **Run the Generator:** Execute the `generate_mirror.py` script to create a local skill for that specific package version.
```bash
python3 <path_to_scripts>/generate_mirror.py <package> <version>
```
3. **Activate the New Skill:** Once generated, a new skill will be available in `.skills/<package>-<version>`.
4. **Use the Grep Map:** Read the `SKILL.md` of the newly created skill. It contains a map of all classes and functions with their exact line ranges.
5. **Targeted Reading:** Use the map to perform surgical `read_file` calls on the files in the `references/` directory of the new skill.
- *Example:* "I see `MyClass.my_method` is in `references/utils.py` lines 120-145. I will read those lines now."
## Core Principles
- **Deterministic:** The map is a direct reflection of the source code (AST-parsed). No LLM interpretation is involved in building the map.
- **Coordinate System:** Use the provided line ranges to avoid reading large files. Only grep exactly what you need.
- **Grounding:** If the package source is available, there is no excuse for API hallucinations.
## Provider Compatibility
This skill is designed to work with any AI agent provider that can execute Python scripts. The output location is configurable for each provider:
| Provider | Default skills path | Auto-detected via env var(s) |
|------------|-----------------------------|-----------------------------------------------------------|
| Claude | `~/.claude/skills` | `ANTHROPIC_API_KEY`, `CLAUDE_API_KEY` |
| Gemini | `~/.gemini/skills` | `GEMINI_API_KEY`, `GOOGLE_GENERATIVEAI_API_KEY` |
| Codex | `~/.copilot/skills` | `CODEX_API_KEY`, `GITHUB_COPILOT_TOKEN` |
| Cursor | `~/.cursor/skills` | — |
| OpenAI | `~/.openai/skills` | `OPENAI_API_KEY` |
| OpenClaw | `~/.openclaw/skills` | — |
| Cline | `~/.cline/skills` | — |
**Configuration priority** (highest wins):
1. `AGENT_SKILLS_PATH` environment variable
2. `skills_path` in `config.json`
3. Provider-specific default (auto-detected or set via `provider` in `config.json` / `AGENT_PROVIDER` env var)
4. `.skills/` in the current working directory
Example `config.json` for explicit provider selection:
```json
{
"provider": "gemini"
}
```
---
*Note: This skill currently supports Python packages via PyPI.*
don't have the plugin yet? install it then click "run inline in claude" again.