A code-review workflow that evaluates a specific branch, commit range, staged change, or pull request. A pull request is a proposed change awaiting review before it is merged.

Use it for merge-readiness reviews and safety checks of concrete code changes. It is not intended for reviewing a whole codebase or a prose-only proposal.

It ties review findings to exact Git versions and checks the change’s scope, risks, supporting claims, and readiness to merge.

anchor-vet — Skill for Claude Code by lynxlangya

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.

Any agent

npx skills add lynxlangya/techne --skill anchor-vet

Clone the repo

git clone --depth 1 https://github.com/lynxlangya/techne

Made for: Claude Code.

Or install techne, the plugin that ships this one along with the rest of its 5 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/lynxlangya/techne/anchor-vet/github.svg)](https://agentmods.dev/skills/lynxlangya/techne/anchor-vet)

Your own site

<a href="https://agentmods.dev/skills/lynxlangya/techne/anchor-vet"><img src="https://agentmods.dev/badge/skills/lynxlangya/techne/anchor-vet/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/lynxlangya/techne/anchor-vet"><img src="https://agentmods.dev/badge/skills/lynxlangya/techne/anchor-vet.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 107 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,283 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

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.

Model	Per session	Once invoked
Fable 5.1	$0.00107	$0.01283
Opus 5	$0.00053	$0.00642
Sonnet 5	$0.00021	$0.00257
Haiku 4.5	$0.00011	$0.00128

Measured 10d ago against content hash 196ca23b721e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

anchor-vet 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 10d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/vet_gate.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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/anchor-vet/SKILL.md · 120 lines

How it starts

The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.

anchor-vet

Force the skipped move in code review: prove the reviewed diff's scope, blast radius, claims, findings, and verdict are anchored to git evidence.

Trigger Check

Use this skill only when there is a concrete code change to judge: a PR, branch, commit range, or staged review target.

Boundary test: can you name a base...head pair of git states whose difference is the artifact under judgment? If yes, use anchor-vet. If no, get the branch or ref first; do not review pasted diffs or prose descriptions.

Do not use anchor-vet for design feedback without a diff, whole-codebase audits, feature implementation, bug fixing, formatting-only tasks, or document review. If the user asks you to fix findings too, render the review verdict first; fixes are a separate task, and behavioral fixes route to anchor-repro.

Forced Procedure

Anchor the scope. Check out the reviewed head locally. Capture external claims before init: for PRs, save the title/body from gh pr view --json title,body --jq '.title + "\n\n" + (.body // "")' to a claims file. Run: python3 skills/anchor-vet/scripts/vet_gate.py init --project <root> --review <slug> --base <ref> --head <ref> --claims-file <path> or, only when there are genuinely no external claims, --no-claims.
Read every hunk. Inspect the full diff and every hunk in scope.json. If the diff is too large to read honestly, stop and propose a split.
Walk the blast radius. For each candidate symbol, read the references found by the gate. Record examined refs with effect and a one-line note. Examined means you opened/read the reference and judged how the change affects it.
Account weak or symbolless hunks. For weak/symbolless hunks, use a verified enclosingUnit when a named unit exists, or file-level with a reason only for genuinely unit-less code/config/prose.
Cross-examine claims. Disposition every anchored claim id from scope.json: verified, contradicted, not-verifiable-from-diff, or non-claim. Verified/contradicted claims need citations.
Hunt findings with severity honesty. Use only blocking, concern, and nit. Cite findings. A blocking finding needs R2 cited evidence or an R3 repro probe. When a behavioral assertion is cheap to demonstrate, record a failing anchor-repro ledger entry against the reviewed head and cite it with entrySha256.
Write and check review.json. Run: python3 skills/anchor-vet/scripts/vet_gate.py check --project <root> --review <slug>. Fix check failures by doing the missing review work, not by padding JSON.
Render the verdict through the gate. Run: python3 skills/anchor-vet/scripts/vet_gate.py close --project <root> --review <slug> --verdict approve|request-changes|blocked. Report the verdict, cite verdict.json, and name each finding's evidence rung.

Read the full file on GitHub · 120 lines

Files

What ships with it

5 files 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.

10d ago First seen · 120 lines · 107 tokens per session scan A 196ca23b721e

Subscribe to this mod's changes

anchor-vet is a skill published in the GitHub repository lynxlangya/techne (105 stars, last pushed 2mo ago), licensed MIT. It adds 107 tokens to every session and 1,283 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 2026-08-30.

Claude Code Code review Git and workflow agent-skills ai-agents codex cursor developer-tools

gentle-ai-collab-perfect

Trigger: contributing to Gentleman-Programming/gentle-ai as an external collaborator. Strict issue-first workflow, honest PR bodies, contributor-vs-maintainer scope, chained-PR strategy, verification protocol, docstring coverage. Load whenever the active repo is Gentleman-Programming/gentle-ai and any part of the…

Gentleman-Programming/gentle-ai · 106 tokens

branch-pr

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work-unit-commits

Plan commits as reviewable work units. Trigger: implementation, commit splitting, chained PRs, or keeping tests and docs with code.

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chained-pr

Trigger: PRs over 400 lines, stacked PRs, review slices. Split oversized changes into chained PRs that protect review focus.

Gentleman-Programming/gentle-ai · 32 tokens

github-pr-creation

Creates GitHub Pull Requests with automated validation and task tracking. Use when user wants to create PR, open pull request, submit for review, or check if ready for PR. Analyzes commits, validates task completion, generates Conventional Commits title and description, suggests labels. NOTE - for merging existing…

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github-pr-review

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anchor-vet

Getting it into your agent

Wrote this? Show the measurements

What it costs to keep this loaded

Grade A, and why

Nothing flagged

How it starts

anchor-vet

Trigger Check

Forced Procedure

What ships with it

What this file has done since we first saw it

Other skills, from other repositories

gentle-ai-collab-perfect

branch-pr

work-unit-commits

chained-pr

github-pr-creation

github-pr-review