Agent skill

Refresh Repo Skill

by VectorSpaceLab in VectorSpaceLab/AREX-Skill

Refreshes an existing repository-specific Agent Skill after the source repository changed.

Apache-2.0Auto-check passed

Install Refresh Repo Skill

skills CLI
$ npx skills add VectorSpaceLab/AREX-Skill --skill refresh-repo-skill -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install VectorSpaceLab/AREX-Skill refresh-repo-skill --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/cli/packages/coding-agent/src/disco/skills/refresh-repo-skill .claude/skills/refresh-repo-skill && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
refresh-repo-skill
GitHub stars
331
Token cost
~3.2k tokens
SKILL.md length
1,505 words
Files
5 (incl. scripts, references)
Skills in repo
157
Repo updated
First seen
Licence
Apache-2.0

At a glance

Refreshes an existing repository-specific Agent Skill after the source repository changed.

  • Works in 9 steps: Resolve the existing skill directory,… → Read… → Produce a staleness audit that separates → …
  • The user says repo code
  • SKILL.md covers Purpose, Inputs, Reference Map and Required Workflow, plus 2 more sections
  • Runs Python scripts from its folder; calls node, python and pip

What it does

Refresh Repo Skill is an agent skill from VectorSpaceLab/AREX-Skill. Refreshes an existing repository-specific Agent Skill after the source repository changed. Use when the user says repo code, APIs, docs, examples, configs, dependencies, or behavior changed and an old skill may now be stale, outdated, inconsistent with current code, or needs to be resynchronized from repository evidence.

Its SKILL.md is about 3.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `references/change-detection-and-staleness-audit.md`, `references/refresh-editing.md` and `references/verification-and-handoff.md`).

The repository describes itself as: A Skill Library for Automated Machine Learning. The licence is Apache-2.0.

When your agent uses it

  • The user says repo code
  • Behavior changed and an old skill may now be stale
  • Inconsistent with current code
  • Needs to be resynchronized from repository evidence

Example prompts

  • “Use the refresh-repo-skill skill to refresh an existing repository-specific Agent Skill after the source repository changed”
  • “/refresh-repo-skill”

Requirements

  • Python 3

Workflow steps

9 steps, taken from the first numbered list in SKILL.md.

  1. Resolve the existing skill directory, current repository path, existing
  2. Read references/change-detection-and-staleness-audit.md.
  3. Produce a staleness audit that separates
  4. If live Python inspection is required and no verified environment exists, use
  5. Read references/refresh-editing.md. Edit the
  6. Resolve and apply the repository license after the refreshed source commit
  7. Update usability test cases under the review/test artifact directory's
  8. Read references/verification-and-handoff.md.
  9. After verification passes, follow verify-repo-skill's structured import

What it can do on your machine

Read from SKILL.md and the folder at commit ac3fe1a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • node
    • python
    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Refresh Repo Skill loads about 3.2k tokens when it runs, and up to ~9.6k if it reads all its reference files. Until then it costs about 85 tokens; SKILL.md has 1,505 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~85
When it runs · the whole SKILL.md, loaded when a task matches
~3.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~9.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from VectorSpaceLab/AREX-Skill at commit ac3fe1a, republished under its Apache-2.0 licence (© VectorSpaceLab). 1,505 words, ~3,238 tokens.

Download SKILL.mdSave it as .claude/skills/refresh-repo-skill/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
refresh-repo-skill
description
Refreshes an existing repository-specific Agent Skill after the source repository changed. Use when the user says repo code, APIs, docs, examples, configs, dependencies, or behavior changed and an old skill may now be stale, outdated, inconsistent with current code, or needs to be resynchronized from repository evidence.
metadata.disco-role
meta

Refresh Repo Skill

Purpose

Use this skill when an existing repo-specific Agent Skill should continue describing the same repository, but the repository itself has changed since the skill was created or last maintained.

Typical requests include:

  • Refresh an old skill after new commits, releases, branches, APIs, CLIs, config formats, examples, or dependencies changed.
  • Audit a skill for stale claims against the current repository code.
  • Update copied references, scripts, workflows, troubleshooting, or usability cases that no longer match the repo.
  • Rebuild the skill's repository evidence without discarding the skill's useful identity, routing, or prior coverage.

This workflow is different from extend-repo-skill: use extend-repo-skill when the user asks to add a new capability or deeper coverage to a working skill. Use this skill when repository drift is the main reason the skill may be wrong.

Inputs

Gather or infer:

  • Existing skill directory containing SKILL.md.
  • Current repository path to use as the source of truth.
  • Existing references/repo-provenance.md from the skill, when present.
  • Optional previous repository baseline, branch, tag, release, commit, or date when the skill has no provenance file.
  • Python inspection environment and installed package name when live API or CLI 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. If the repository path is missing and cannot be inferred from the current working directory or user request, ask for it.

Reference Map

Read these references as the workflow reaches each stage:

Use scripts/check_repo_provenance.py when references/repo-provenance.md exists. It compares the skill snapshot with the current Git checkout and prints JSON with current, stale, or unknown status.

When useful, also read sibling workflow-skill references:

  • ../create-repo-skill/references/ for repository evidence discovery, installed-package inspection, and output structure.
  • ../verify-repo-skill/references/ for usability case format, verification review, and import/index routing guidance.
  • ../extend-repo-skill/references/ for narrow editing and regression review rules.
  • ../prepare-repo-skill-env/SKILL.md if live Python inspection is needed and no verified environment is available.

Required Workflow

  1. Resolve the existing skill directory, current repository path, existing references/repo-provenance.md baseline, optional user-provided baseline, Python inspection context, review/test artifact directory, and review output path. 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 temporary working directory outside <agent-dir>/skills/ before editing. Keep that working copy until the dedicated importer succeeds; never edit the live managed copy in place.

  2. Read references/change-detection-and-staleness-audit.md. Build a current-state map of the existing skill. When provenance exists, run python scripts/check_repo_provenance.py --skill-dir <skill_dir> --repo-path <repo_path> from this workflow-skill directory or adapt the script path to the installed skill copy. Use its JSON output as the first staleness signal, then gather current repository evidence and optional change evidence from Git history or release notes.

  3. Produce a staleness audit that separates:

    • Claims still supported by current repo evidence.
    • Claims that are stale, removed, renamed, or behaviorally changed.
    • New repo capabilities that should be represented because they replace or materially alter existing skill guidance.
    • Unknowns requiring live inspection or user clarification.
  4. If live Python inspection is required and no verified environment exists, use prepare-repo-skill-env to create or repair one, then continue only from its verified handoff.

  5. Read references/refresh-editing.md. Edit the resolved runtime working copy in place. Preserve root and sub-skill identities unless the user explicitly asks for a rename or the current name is invalid. Add or update references/repo-provenance.md with the refreshed source snapshot. Preserve the canonical repo_id and skill_id by default. Treat the existing area-family assignments as the routing baseline: keep them when the repository's capability scope is unchanged, but do not keep them blindly when the refresh adds, removes, or materially changes a capability. If the capability scope changed, the taxonomy hash changed, or the user requests reclassification, produce a new external area-family routing handoff and matching minimal v2 metadata before import. Do not hand-edit generated router Markdown or silently change assignments in prose.

  6. Resolve and apply the repository license after the refreshed source commit is known and before handing the tree to 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 refresh; do not preserve a stale license solely because it was present in the previous skill. Update all root/sub-skill frontmatter to the same result. Preserve NOASSERTION when GitHub returns it; normalize only unavailable results to NO_LICENSE, keep the report outside the runtime tree, and carry old value, new value, source commit, status, and reason into the handoff. NO_LICENSE is a warning and not a legal conclusion.

  7. Update usability test cases under the review/test artifact directory's test-cases/ subtree so at least one case proves refreshed behavior and at least one case guards a pre-existing workflow that should remain valid.

  8. Read references/verification-and-handoff.md. Verify that refreshed public skill content is self-contained, current, privacy-safe, and reachable from nearby SKILL.md files. Save staleness audits, verification reports, and human-review notes under the review/test artifact directory's reports/ subtree.

  9. After verification passes, follow verify-repo-skill's structured import policy: use ask_user_question when approval is still required, then run the approved or auto-authorized refresh through verify-repo-skill/scripts/import_repo_skill.mjs with --overwrite, the refreshed runtime skill 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. Use --overwrite only because this workflow is updating that exact approved repo skill. The helper installs the refreshed runtime tree under ~/.disco/agent/skills/repositories/repo-skills/<skill-id>/, rebuilds the sibling live DisCo repo-skills-router under the global lock, and restores both on failure. Do not hand-edit router Markdown or manually combine copy and updater commands. The refreshed skill is directly available to DisCo Researcher in a new session; use import-repo-skills-to-agent only when the user explicitly asks for a cross-agent export.

Show full SKILL.md (485 more words)Show less

Non-Negotiables

  • Treat the current repository as the source of truth; do not preserve old skill claims just because they were previously useful.
  • Do not regenerate a replacement skill from scratch unless the user explicitly asks or the old skill is so structurally invalid that in-place repair would be misleading.
  • Do not edit a live skill under <agent-dir>/skills/repositories/repo-skills/ before the global import lock is held. Refresh an external working copy, then let verify-repo-skill/scripts/import_repo_skill.mjs replace the live target.
  • Do not finish a refresh without references/repo-provenance.md; if the old skill lacks it, create it from the current repository snapshot.
  • Do not silently change a repository's repo_id or skill_id during a refresh. A rename is a separate identity migration and must update the central repository index and all router references together.
  • Do not silently change area-family assignments. Preserve the prior routing when capability scope is unchanged; otherwise use the verified external routing handoff and minimal v2 metadata, then let the locked importer update the router and indexes atomically.
  • Do not change the skill's public purpose to cover unrelated new repository areas unless those areas replace or materially affect existing guidance.
  • Do not add claims about APIs, CLIs, configs, data formats, dependency behavior, or runtime behavior without current repository evidence or live inspection.
  • Do not leak local checkout paths, Python executable paths, conda or virtualenv names, pip show locations, API keys, or machine-specific details into public skill files.
  • Do not link runtime skill documentation to the source repository checkout. Distill current facts into the skill directory.
  • Do not preserve or reintroduce runtime instructions that refer to source repo scripts, examples, notebooks, tools, or configs by path. If the refreshed skill still needs that behavior, add a bundled replacement under the skill's own scripts/ or references/ tree and link it instead.
  • Do not treat tests/ as a skill directory. It is the review/test artifact area.
  • Do not write staleness audits, 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:

  • A runtime working copy refreshed against current repository evidence, followed by a locked live replacement when import is approved or auto-authorized.
  • An updated references/repo-provenance.md snapshot that future agents can use to detect whether the skill may be stale.
  • A staleness audit and review package under the review/test artifact directory's reports/ subtree that identifies changed, retained, and removed guidance.
  • Updated references, scripts, sub-skills, and usability test cases where the old skill was stale.
  • Verification evidence showing the public skill no longer depends on outdated repo facts.
  • A routing handoff stating whether prior area-family assignments were preserved or reclassified, with the reason and evidence for any change.
  • A final handoff that distinguishes refreshed public skill content, review/test artifacts, evidence used, and any accepted uncertainty.

© VectorSpaceLab, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts, references) in cli/packages/coding-agent/src/disco/skills/refresh-repo-skill of VectorSpaceLab/AREX-Skill.

  • SKILL.md
  • references/change-detection-and-staleness-audit.md
  • references/refresh-editing.md
  • references/verification-and-handoff.md
  • scripts/check_repo_provenance.py

Open the folder on GitHubat commit ac3fe1a

Compare with similar skills

Refresh Repo Skill next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Refresh Repo Skill compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Refresh Repo Skill this skillVectorSpaceLab/AREX-Skill331—~3.2kAutomated safety check: PassApache-2.0
Index Refreshpaperclipai/paperclip99k—~994Automated safety check: PassMIT
Make Changesremix-run/remix33k—~2.4kAutomated safety check: PassMIT
Orch Change Featureaffaan-m/ECC276k1 repos~420Automated safety check: PassMIT
Meta Refreshthedaviddias/Front-End-Checklist74k—~434Automated safety check: PassMIT
Change Managementsickn33/agentic-awesome-skills47k2 repos~3.5kAutomated safety check: PassMIT

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Questions about Refresh Repo Skill

What does Refresh Repo Skill do?

Refreshes an existing repository-specific Agent Skill after the source repository changed. Refresh Repo Skill is an agent skill from VectorSpaceLab/AREX-Skill. Refreshes an existing repository-specific Agent Skill after the source repository changed.

When should I use Refresh Repo Skill?

Refresh Repo Skill fits situations like: the user says repo code; behavior changed and an old skill may now be stale; inconsistent with current code; needs to be resynchronized from repository evidence.

How do I install Refresh Repo Skill in Claude Code?

Run `npx skills add VectorSpaceLab/AREX-Skill --skill refresh-repo-skill -a claude-code`. Or copy the skill folder (cli/packages/coding-agent/src/disco/skills/refresh-repo-skill in VectorSpaceLab/AREX-Skill) into .claude/skills/refresh-repo-skill in your project. Claude Code loads it when a task matches its description.

How do I install Refresh Repo Skill in Codex?

Run `npx skills add VectorSpaceLab/AREX-Skill --skill refresh-repo-skill -a codex`. Or copy the skill folder (cli/packages/coding-agent/src/disco/skills/refresh-repo-skill in VectorSpaceLab/AREX-Skill) into .agents/skills/refresh-repo-skill in your project. Codex loads it when a task matches its description.

Can I use Refresh Repo Skill in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add VectorSpaceLab/AREX-Skill --skill refresh-repo-skill -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/refresh-repo-skill, .gemini/skills/refresh-repo-skill, .github/skills/refresh-repo-skill and .opencode/skills/refresh-repo-skill in your project.

What does Refresh Repo Skill need to run?

Going by SKILL.md and its folder, Refresh Repo Skill needs Python for the scripts in its folder and the command-line tools its instructions call (node, python and pip). Our summary lists: Python 3.

Does Refresh Repo Skill access the network?

SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Refresh Repo Skill safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Refresh Repo Skill use?

Refresh Repo Skill is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Refresh Repo Skill use?

About 3.2k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 6.3k tokens, read only when the agent opens those files.

What are the alternatives to Refresh Repo Skill?

Skills that share tags, products or a category with Refresh Repo Skill: Index Refresh (paperclipai/paperclip, 99k stars), Make Changes (remix-run/remix, 33k stars), Orch Change Feature (affaan-m/ECC, 276k stars) and Meta Refresh (thedaviddias/Front-End-Checklist, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Refresh Repo Skill?

VectorSpaceLab (a GitHub organization) maintains it in VectorSpaceLab/AREX-Skill, which has 331 GitHub stars. The repository holds 157 skills in this directory. The repository was last updated on September 3, 2026.

Source: VectorSpaceLab/AREX-Skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.