skill-graph-for-analogical-reasoning

Skill Graph for Analogical Reasoning. Build a graph over SKILL.md skills, choose one primary skill, and retrieve complementary support instead of naively attaching top similar skills.

Use this skill when the user wants to work with a graph skill over local SKILL.md folders.

This skill is for:

• graph-based skill indexing
• analogical reasoning and transfer
• one primary skill plus complementary support
• avoiding naive "top similar skills" retrieval

The full Python package and CLI for this project are available in the GitHub repository.

What this skill does

This skill wraps the grap-skill capability.

It supports three primary commands:

• /grap-skill build
• /grap-skill query
• /grap-skill look

Core rule

• build is the only command that may scan skill folders and update the graph.
• query and look are read-only against an existing graph.json.
• Do not silently rebuild during query.

Code-backed usage

This skill is allowed to call code.

The python3 {baseDir}/scripts/run_grap_skill.py ... commands below are the stable execution entrypoints intended for the skill runtime and for model-driven tool use. They let the skill call a controlled wrapper inside the installed skill bundle instead of relying on ad hoc shell reconstruction.

Preferred execution order:

1. Use the helper script in {baseDir}/scripts/run_grap_skill.py.
2. If the Python package is installed in the current interpreter, the wrapper may use python -m auto_grap_skill.
3. If neither bundled code nor the local Python package is available, direct the user to the GitHub repository for this project and install the Python package first.

Primary commands

/grap-skill build

bash

python3 {baseDir}/scripts/run_grap_skill.py build --source <skills_dir> --output <graph_dir>

Example:

bash

python3 {baseDir}/scripts/run_grap_skill.py build --source ./skills-main --output ./.grap-skill

/grap-skill query

bash

python3 {baseDir}/scripts/run_grap_skill.py query "<task text>" --graph <graph_json_path>

Example:

bash

python3 {baseDir}/scripts/run_grap_skill.py query "edit a docx file with comments" --graph ./.grap-skill/graph.json

/grap-skill look

bash

python3 {baseDir}/scripts/run_grap_skill.py look --graph <graph_json_path> --output <html_path>

Example:

bash

python3 {baseDir}/scripts/run_grap_skill.py look --graph ./.grap-skill/graph.json --output ./.grap-skill/graph-look.html

How to interpret results

• primary_skill is the execution center.
• Always treat primary_skill as the default lead. Use a supporting_skill only if it adds clear missing coverage and does not conflict with or dilute the primary skill. If a suggested supporting skill is not actually helpful for the current task, do not adopt it.
• supporting_skills are the only skills that should normally supplement the primary skill in context.
• fallback_skills are substitutes for failure paths.
• similar_skills are for graph browsing, not default prompt context.

Why this is different

Most retrieval systems stop at similarity. This one tries to separate:

• the skill that should lead execution
• the skills that add complementary coverage
• the skills that are merely nearby or redundant

That is the whole analogical-reasoning goal of this project.

More files in this skill

• README.md — human-facing usage and install notes
• reference.md — algorithm and result interpretation
• scripts/run_grap_skill.py — helper wrapper that calls the actual Python package/CLI

GitHub version

The GitHub release of this project should also point users back to this skill bundle for skill-style installation:

• ClawHub/OpenClaw install: openclaw skills install skill-graph-for-analogical-reasoning
• GitHub/Python install: use the repository's Python package and local CLI when a full source checkout is preferred