skill-installer
Use when listing or installing Codex skills from curated sources, GitHub repo paths, private repos, or local package locations.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
菜单
Use when listing or installing Codex skills from curated sources, GitHub repo paths, private repos, or local package locations.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
Review changed code for behavior-preserving simplification by removing dead code, eliminating duplication, extracting shared helpers, improving names, and tightening tests. Use when a user asks for code review, refactor, clean up PR, simplify, tidy up code, review my changes, or maintainability cleanup before merge.
Check if a repository or agent-facing product surface is ready for AI coding agents. Use when you need to audit repo agent compatibility, review AGENTS.md, find missing test/build commands, evaluate docs quality, assess tool/action parity, or produce a file-evidence scorecard with specific fixes.
Use when reviewing, creating, shrinking, or refactoring AGENTS.md and directly linked instruction guidance that need scoped routing, deduplication, contradiction resolution, or progressive disclosure.
Review code architecture, code quality, dependency graphs, coupling, technical debt, modularization, ownership, and test seams. Use when refactors, restructuring, tightly coupled code, or architecture decisions need proof-backed options.
Choose validation proof for tests, CI, coverage, evals, and closeout evidence: map changed files to repo-native commands, classify pass/fail/blocked ownership, preserve trace/regression artifacts, and keep local, CI, Tessl, external-review, tracker, and runtime truth separate. Use when users ask what tests to run, why validation failed, what proof is enough, or whether command evidence supports a claim.
Defensive review of AI-agent skills, plugins, and tools using Liran Tal's security principles. Use when assessing provenance, permissions, data exposure, sandboxing, or approval boundaries before adoption.
| name | skill-installer |
| description | Use when listing or installing Codex skills from curated sources, GitHub repo paths, private repos, or local package locations. |
| metadata | {"short-description":"Install curated skills from openai/skills or other repos"} |
Install the smallest requested skill set, prove where it landed, and keep source, destination, and runtime visibility separate. By default these are from https://github.com/openai/skills/tree/main/skills/.curated, but users can also provide other locations. Experimental skills live in https://github.com/openai/skills/tree/main/skills/.experimental and can be installed the same way.
Treat installation as a provenance and visibility workflow, not a file copy. List before installing when the user has not named a skill, install only the named package, and report validation as pass, fail, or blocked with the exact source and destination.
Adapt the route to the source: curated names, experimental names, public GitHub paths, and private repo paths need different commands and blocker language. Keep the install surface narrow even when the user mentions several catalogs.
Use the helper scripts based on the task:
.curated, but you can pass --path skills/.experimental when they ask about experimental skills.Install skills with the helper scripts.
When listing skills, output approximately as follows, depending on the context of the user's request. If they ask about experimental skills, list from .experimental instead of .curated and label the source accordingly:
"""
Skills from {repo}:
After installing a skill, tell the user: "Restart Codex to pick up new skills."
All of these scripts use network, so when running in the sandbox, request escalation when running them.
scripts/list-skills.py (prints skills list with installed annotations)scripts/list-skills.py --format jsonscripts/list-skills.py --path skills/.experimentalscripts/install-skill-from-github.py --repo <owner>/<repo> --path <path/to/skill> [<path/to/skill> ...]scripts/install-skill-from-github.py --url https://github.com/<owner>/<repo>/tree/<ref>/<path>scripts/install-skill-from-github.py --repo openai/skills --path skills/.experimental/<skill-name>User: "What skills can I install from the curated catalog?"
Action: run scripts/list-skills.py --format json, then summarize available
skills and installed annotations.
User: "Install the GitHub skill at this repo path."
Action: run scripts/install-skill-from-github.py --url <url>, then report
source, destination, validation, and restart guidance.
$CODEX_HOME/skills/<skill-name> (defaults to ~/.codex/skills).--path values install multiple skills in one run, each named from the path basename unless --name is supplied.--ref <ref> (default main), --dest <path>, --method auto|download|git.When installing into an SDK-aware repository, preserve and validate the skill package contract after download:
./bin/ask sdk start <installed-path-or-handle> --json --robot once
the package path exists; the start receipt is the shared lifecycle authority
for install, update, skillify, refactor, and builder lanes.SKILL.md with name and description.agents/openai.yaml when present; do not move SDK contract fields
into it.references/contract.yaml when present. If the repo enforces
strict SDK readiness and this file is missing, classify the install as
blocked_validation rather than silently accepting the package../bin/ask skills package verify <installed-path-or-handle> --json --robot
when available.
Treat reference_quality blockers, including reference_heading_invocable
failures for Markdown references or vendored KnowledgeOS capsules, as
install validation blockers.package_contract.sdk_contract.required_fields.missing as blocking
for strict SDK installation. Required SDK fields are purpose, inputs,
outputs, permission profile, evals, and evidence policy.~/.agents/ OTEL, session, or observability providers only as
evidence enrichment. They do not replace install artifacts, evals, or
package validators.--execute, Tessl live-private dry-run, and handoff-readiness.https://github.com/openai/skills/tree/main/skills/.curated via the GitHub API. If it is unavailable, explain the error and exit.GITHUB_TOKEN/GH_TOKEN for download.$CODEX_HOME/skills.references/contract.yamlreferences/evals.yamlreferences/skill-factory/install-flows.mdreferences/skill-factory/troubleshooting.md