Extend Repo Skill logo

Extend Repo Skill

Organization
VectorSpaceLab
extend-repo-skill

Extends an existing repository-specific Agent Skill with new capabilities, deeper coverage, troubleshooting, scripts, and usability tests. Use when the user asks to expand, improve, deepen, or add coverage to an already implemented skill instead of creating a new skill from scratch. If the repository itself changed and the old skill may be stale, use refresh-repo-skill instead.

Overview

PublisherVectorSpaceLab
RepositoryAREX-Skill
Skill nameextend-repo-skill
Stars
341
Forks
26
Bundled files
3
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by VectorSpaceLab on GitHub. Read the source before you install it.

Installation

Install the Extend Repo Skill AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/VectorSpaceLab/AREX-Skill/tree/main/cli/packages/coding-agent/src/disco/skills/extend-repo-skill
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git /tmp/AREX-Skill
mkdir -p .claude/skills
cp -r /tmp/AREX-Skill/cli/packages/coding-agent/src/disco/skills/extend-repo-skill .claude/skills/extend-repo-skill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Extend Repo Skill in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Extend Repo Skill on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Extend Repo Skill is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Extend Repo Skill

Purpose

Use this skill when the user already has a generated or hand-written Agent Skill and wants to expand it without losing the useful behavior it already provides.

Typical requests include:

  • Add support for a new repo feature, public API, CLI, workflow, model family, config format, or troubleshooting path that the user specifically wants covered.
  • Improve thin references, missing scripts, poor routing, incomplete usability tests, or unclear triggering.
  • Extend an existing skill for a larger repo instead of regenerating it from scratch.

If the user's main concern is that the repository code, docs, APIs, CLIs, configs, or dependencies changed and the old skill may be stale, use the sibling refresh-repo-skill skill instead.

The expected result is an edited runtime skill directory plus updated usability test cases and a verification/human-review package under the skill's review/test artifact directory. Do not create a separate replacement skill unless the user explicitly asks for a fork.

Inputs

Gather or infer:

  • Existing skill directory containing SKILL.md.
  • Resolved DisCo agent directory, normally ~/.disco/agent or the active DISCO_CODING_AGENT_DIR, when the existing skill may be a live managed copy.
  • Repository path used as the evidence source for the extension.
  • The user's requested new capability, failure mode, coverage gap, or quality improvement.
  • Python inspection environment and installed package name when live API verification is needed.
  • Existing review/test artifact directory, if any.
  • Desired review/test artifact output directory, if the user has a preference.

If the existing skill directory is missing or does not contain SKILL.md, stop and ask for the correct skill path.

Reference Map

Read these references as the workflow reaches each stage:

When useful, also read sibling workflow-skill references: ../create-repo-skill/references/ for canonical skill IDs, repository evidence discovery, installed-package inspection, planning, and writing, and ../verify-repo-skill/references/ for usability test-case format, verification review, and import/index routing guidance.

Required Workflow

  1. Resolve the existing skill directory, repository path, requested extension, DisCo agent directory, and review/test artifact directory. If the user does not specify an artifact directory, default to <repository-path>/skills/tests/<skill-id>/, with usability cases under test-cases/ and review reports under reports/. If the existing skill is the live managed copy under <agent-dir>/skills/repositories/repo-skills/<skill-id>/, copy only its runtime tree to a working directory outside <agent-dir>/skills/, preserving the <skill-id> directory basename. Keep that working copy until the dedicated importer succeeds; never edit the live managed copy in place.

  2. Read references/extension-planning.md. Audit current root/sub-skill routing, bundled references, bundled scripts, evals, usability tests, and known gaps before editing.

  3. Gather targeted repository evidence for the requested extension. Use source code plus installed-package inspection for API facts; use docs, examples, tests, and configs for intent and workflows.

  4. Write a concise extension plan that maps each new or changed capability to exactly one skill location, reference, script, or usability case.

  5. Read references/editing-and-versioning.md. Edit the resolved source or external working copy while preserving useful current guidance, frontmatter IDs, and public structure. Preserve the canonical repo_id and skill_id unless the user explicitly requests an identity migration. Treat the current area-family assignments as the baseline. If the extension is only deeper coverage of already routed capabilities, retain those assignments. If it adds a distinct capability, removes a capability, changes the repository's scope, changes the taxonomy hash, or the user requests reclassification, create a new external area-family routing handoff with assignment-specific evidence and update the minimal v2 metadata to match it. Never hand-edit generated family pages or silently change routing in the skill prose.

  6. Resolve and apply the repository license after the extension source commit is known and before verification:

    bash
    node ../verify-repo-skill/scripts/resolve_repo_license.mjs \
      --repository <owner/repository> \
      --source-commit <40-hex-source-commit> \
      --json > <artifact-root>/reports/license-resolution.json
    node ../verify-repo-skill/scripts/apply_repo_license.mjs \
      --skill-dir <external-runtime-skill-dir> \
      --license <value-from-report>

    Re-query on every extension and synchronize the one returned value over the complete root/sub-skill tree. Record old value, new value, source commit, status, and reason in the handoff. Preserve NOASSERTION as the accepted source value and use NO_LICENSE only when the resolver is unavailable; this fallback is a warning, not a legal conclusion, and does not by itself block verification or import.

  7. Add or update usability test cases for the new capability and at least one regression-sensitive existing workflow under test-cases/ in the review/test artifact directory.

  8. Read references/verification-and-handoff.md. Run automatic verification, create a human review package under reports/ in the review/test artifact directory, and fix blocking issues.

  9. After verification passes, follow verify-repo-skill's structured import policy. Ask for import or overwrite approval unless the user already authorized that exact action, then run verify-repo-skill/scripts/import_repo_skill.mjs with the verified external runtime directory and --routing-entry <repo-path>/skills/disco/routing_decision/classification.json. The external handoff is mandatory for a normal classified import, even when the existing area-family assignments are retained. Pass --overwrite only for the exact approved existing managed skill. The importer installs the runtime tree and rebuilds the sibling live repo-skills-router under one rollback-capable global lock. After success, DisCo Researcher can use the extended skill in a new session; use import-repo-skills-to-agent only for an explicitly requested cross-agent export.

Non-Negotiables

  • Do not discard and rewrite the whole skill just because the extension is easier to express from scratch.
  • Do not edit a live skill under <agent-dir>/skills/repositories/repo-skills/ directly. Extend an external working copy, then let verify-repo-skill/scripts/import_repo_skill.mjs replace the approved live target.
  • Do not install an extended repo skill through a manually assembled copy and router-update sequence.
  • Do not rename root or sub-skill IDs unless the user explicitly asks or the current names are invalid.
  • Do not silently change a repository's repo_id or skill_id; identity changes are separate migrations that must update the central repository index and all router references together.
  • Do not silently change area-family assignments. Preserve them for a same-scope extension, and use the verified routing handoff plus the locked importer when the extension changes capability scope or requires reclassification.
  • Do not remove existing references, scripts, routes, or usability cases unless they are wrong, stale, duplicated, or replaced by a better self-contained artifact.
  • Do not add claims about APIs, CLIs, configs, data formats, or runtime behavior without repository evidence or live inspection.
  • Do not leak local checkout paths, Python executable paths, virtualenv or conda names, pip show locations, or machine-specific details into public skill files.
  • Do not link runtime skill documentation to original repo docs, examples, notebooks, or scripts. Distill or adapt material into the skill directory.
  • Do not leave new or existing runtime guidance that tells future agents to run, read, or adapt source repo scripts by path. Bundle the needed script, wrapper, or distilled recipe inside the skill's own scripts/ or references/ tree before linking it.
  • Do not treat tests/ as a skill directory. It is the review/test artifact area.
  • Do not write evals/, verification reports, human-review notes, publication checklists, prompt samples, benchmark notes, or other check-only artifacts inside the runtime skill directory. Put concrete usability cases under the review/test artifact directory's test-cases/ subtree and reports under its reports/ subtree, defaulting to <repository-path>/skills/tests/<skill-id>/.

Output Summary

By the end, the user should have:

  • The source skill directory or external working copy updated without mutating a live managed skill outside the import transaction.
  • New or revised references/scripts/sub-skills where the requested capability needs depth.
  • Updated usability test cases in the configured review/test artifact directory's test-cases/ subtree.
  • An automatic verification report and human review package in the configured review/test artifact directory's reports/ subtree.
  • An approved managed import that DisCo Researcher can use directly in a new session, or a clear staged-only status when import was declined.
  • A routing handoff that records whether the existing assignments were preserved or reclassified, including evidence for any changed assignment.
  • A final handoff that distinguishes changed public skill content, review/test artifacts, evidence used, import status, and remaining gaps.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Extend Repo Skill AI skill do?

Extends an existing repository-specific Agent Skill with new capabilities, deeper coverage, troubleshooting, scripts, and usability tests. Use when the user asks to expand, improve, deepen, or add coverage to an already implemented skill instead of creating a new skill from scratch. If the repository itself changed and the old skill may be stale, use refresh-repo-skill instead.

Why use Extend Repo Skill on TypingMind?

Because you install it once and use it with any model. Extend Repo Skill is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Extend Repo Skill in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/VectorSpaceLab/AREX-Skill/tree/main/cli/packages/coding-agent/src/disco/skills/extend-repo-skill. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Extend Repo Skill?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Extend Repo Skill?

As many as you like. As long as a model supports skills, you can use Extend Repo Skill with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Extend Repo Skill AI skill free?

Yes. It is published on GitHub by VectorSpaceLab under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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