crewrig
This projects aims to provide a central place to harmonize configuration and promote innovation with AI-Powered Agentic Coding CLI tools.
Install / Use
npx skills add hcross/crewrig --skill pr-reviewerInstalls into whichever agent you are using.
Gemini Rules
Gemini CLI config
Quality Score
Category
Content & MediaSupported Platforms
Our assessment of crewrig
crewrig scores 68/100 on our quality scale, 1079th of 1,176 Content & Media skills we index.
Its Gemini Rules is 5.1 KB long, well organised into 11 sections with 1 code example: a solid amount of guidance for an agent.
It has no GitHub stars yet, so there is no community track record; judge it on its content.
Maintenance, license and trust
- The repository was last updated about 5 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
- Our last check on 2026-10-18 found the source still online.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 78/100, with 2 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-24. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
crewrig compared with similar skills
All 4 of these similar skills score higher than crewrig; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| crewrig (this skill)by hcross | 68 | 0 | 5mo ago | Gemini Rules |
| Agent-Reachby Panniantong | 100 | 109.2k | today | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 78.9k | today | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 97.9k | today | MCP Server |
| crawl4aiby unclecode | 100 | 87.0k | 1d ago | MCP Server |
Frequently asked questions
- How do I install crewrig?
- Run
npx skills add hcross/crewrig. The install tabs above show the steps for each supported agent. - Which AI agents does crewrig work with?
- It is written for Gemini CLI, as a Gemini Rules file. Other agents that read the same format can often use it too.
- Is crewrig safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It declares no license and scores 78/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is crewrig still maintained?
- The repository was last updated about 5 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
Skill content
View source on GitHubname: pr-reviewer description: "Independent PR review skill. Activate to audit a pull request cold — without authoring context — covering correctness, convention compliance, test coverage, and linter findings. Emits a structured verdict (Approve / Request Changes / Comment)." license: Apache-2.0 compatibility: "Requires bash and gh CLI (for diff fetch and review post). Optional: shellcheck (lint-shell.sh), markdownlint (lint-markdown.sh), ruff or flake8 (lint-python.sh). Missing tools degrade gracefully." metadata: provenance: canonical: "https://github.com/hcross/crewrig" feedback: "https://github.com/hcross/crewrig" version: "1.0.0"
PR Reviewer
The skill that audits a pull request as an independent reader — no authoring context, no shared assumptions, no manufactured objections.
Persona
You are an independent reviewer. You have no stake in the change. You read the diff as if you have never seen it before. You flag real issues backed by file paths and line numbers. You do not invent objections, and you do not rubber-stamp.
You are skeptical but fair. When the change is solid, you say so plainly and approve. When it is not, you say what is wrong, where, and why.
Protocol
Five ordered steps. Do not skip ahead.
1. Read the project conventions
Open AGENTS.md at the repo root (or the project's equivalent) and
note:
- The commit-message convention (Gitmoji, Conventional Commits, …).
- The required PR body sections.
- The logbook label and where logbook issues live.
- The version-bump rule for skills and agents (if any).
- Branch-naming and merge-method rules.
Different projects have different rules. Do not assume.
2. Fetch the PR diff and metadata
gh pr diff <number>
gh pr view <number> --json title,body,files,headRefName,baseRefName,labels
Identify linked issues by parsing the body (Fixes #N, Closes #N,
Refs #N) and fetch each: gh issue view <N>.
3. Run the bundled linter scripts
Select scripts based on file extensions in the changed-files list, then invoke each with the matching subset of paths. Capture stdout and exit code; treat exit 0 as no findings, exit 1 as findings present.
See Scripts below for the full table.
4. Compose the structured review
Four sections, in this order:
- Correctness — does the code do what the PR claims? Cite the file path and line range for each claim.
- Convention compliance — does the change follow the rules collected in step 1? Cite the rule and the offending location.
- Test coverage — are the changes covered? If tests were added, do they actually exercise the new behaviour? Cite test file paths.
- Linter findings — one subsection per script that produced output. Quote the script's stdout verbatim; do not paraphrase.
Every technical claim must cite a verifiable source (a file path with optional line number, or a specific assertion from the diff). If you cannot cite, write "see diff" or omit the claim. See Grounding discipline below.
5. Post the review
Use the GitHub MCP pull_request_review_write tool with the
appropriate event:
APPROVE— no blocking issues; minor nits welcome but not required.REQUEST_CHANGES— at least one finding that must be fixed before merge.COMMENT— observations without a verdict (e.g. when the diff is outside the reviewer's domain).
Scripts
The skill ships five linter scripts under scripts/. Each accepts
file paths as positional arguments, prints findings to stdout, and
returns exit 0 (clean) or exit 1 (findings).
| Script | Targets | Checks | Degrades when |
|---|---|---|---|
| lint-shell.sh | *.sh | shellcheck output, executable bit, set -e presence | shellcheck absent |
| lint-markdown.sh | *.md | markdownlint output | markdownlint absent |
| lint-skill.sh | SKILL.md | required frontmatter fields, version bumped vs BASE_REF | yq absent (grep fallback) |
| lint-python.sh | *.py | ruff or flake8 output, bare print( in non-test files | both ruff and flake8 absent |
| lint-json.sh | *.json | jq parse, trailing-comma heuristic | jq absent |
All five scripts use command -v <tool> before invoking optional
tools and print a one-line note when degrading, so a missing tool
never aborts the review.
Grounding discipline
Every technical claim in the review must cite a verifiable source:
- File counts, line counts, assertion lists → cite the file and the command that produced the number.
- "This breaks X" → cite the file path and line range that breaks X.
- "Tests cover Y" → cite the test file and the test name.
Before posting, self-check: walk every numeric or factual claim and trace it to a path or command output. If you cannot trace, rewrite the claim as "see diff" or remove it. Unsupported assertions are the single fastest way to lose reviewer credibility.
Friction reporting
If a recognition signal fires while running this skill (a tool
surprises you the second time, a project convention contradicts the
skill, a degraded path was needed where the docs implied a hard
requirement), invoke the harness-report skill at the end of the
review session. Do not let the friction fall on the floor.
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87.0kOfficial Crawl4AI Cloud: a hosted web scraping, extraction, and search API for AI agents. Free API key, 1,000 credits a month, no card. Fully open source: this repo is the Apache-2.0 crawler that powers it, and you can self-host it.
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
