gr

A workflow for reviewing a pull request with Greptile, fixing actionable findings, waiting for checks, merging the change, deploying it, and verifying the running production version.

In plain words
What is it for?
Use it to take an existing pull request through final review and into a verified production deployment.
Why use it?
It keeps code review, automated checks, merging, deployment, and production verification in one tracked process.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/mrmps/chomsky-stack/gr
Any agent
npx skills add mrmps/chomsky-stack --skill gr
Clone the repo
git clone --depth 1 https://github.com/mrmps/chomsky-stack

Made for: Claude Code, Codex.

Per session 95 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,257 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00095 $0.01257
Opus 5 $0.00048 $0.00629
Sonnet 5 $0.00019 $0.00251
Haiku 4.5 $0.00010 $0.00126

Measured yesterday against content hash 438ccb386615, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

gr scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/gr/SKILL.md · 70 lines

How it starts

The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Greptile Review, Merge, and Deploy

Take the current PR from review through verified production deployment. Keep working until Greptile has no actionable findings, every current check is terminal without failures, GitHub reports the PR merged, the merged revision is deployed through the repository's documented production path, and production verification passes. A check being non-required does not make its failure safe to ignore.

Resolve the PR and base

  1. Read repository instructions and inspect the worktree before changing anything. Preserve unrelated user changes.
  2. Resolve the current PR with gh pr view --json number,url,headRefName,baseRefName,mergeStateStatus,statusCheckRollup.
  3. Fetch the PR base and head from origin.
  4. Review against origin/<baseRefName>, never a possibly stale local base branch. Confirm the diff with git diff --stat origin/<baseRefName>...HEAD.
  5. If the branch is behind its remote base, rebase or merge according to repository convention before the final review. Use guarded force-pushes (--force-with-lease) after rebasing.

Run Greptile

  1. Confirm the CLI is available and authenticated with greptile --version and greptile whoami.

  2. Inspect repository review rules with greptile config.

  3. Run a fresh machine-readable review:

    greptile review -b origin/<baseRefName> --json --instructions "Review rigorously for correctness, security, lifecycle races, data loss, performance regressions, error handling, and missing tests. Report every actionable issue; omit stylistic preferences."
    
  4. If Greptile reports an implausibly large diff, stop that run and fix base resolution. Do not split valid work merely to satisfy a review computed against stale local main.

  5. Use greptile review --resume only for an explicitly unfinished review. Use a fresh review after code changes.

Address findings

For every finding:

  1. Inspect the referenced code and surrounding contract.
  2. Classify it as actionable or false positive using concrete evidence.
  3. Fix actionable issues at the owning abstraction, add regression coverage, and avoid unrelated cleanup.
  4. Retain a concise evidence note for false positives; do not change correct code merely to silence a reviewer.
  5. Run focused tests after each logical fix.

Read the full file on GitHub · 70 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 70 lines · 95 tokens per session scan A 438ccb386615

Subscribe to this mod's changes

gr is a skill published in the GitHub repository mrmps/chomsky-stack (7 stars, last pushed 3d ago), licensed MIT. It adds 95 tokens to every session and 1,257 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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