Evidence-gated diff review for PRs, branches, commit ranges, staged code changes, and merge readiness checks. Use when an AI reviewer must review a concrete git-anchored diff, judge whether code is safe to merge, inspect a PR URL or branch, cross-examine PR or commit claims, account blast radius, or render approve/request-changes/blocked verdicts. Do not use for design-only review, whole-codebase audits, bug fixing, or code authoring without a git diff under judgment.
npx skills add https://github.com/lynxlangya/techne --skill 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.
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.
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.
scope.json.If the diff is too large to read honestly, stop and propose a split.
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.
verified enclosingUnit when a named unit exists, or file-level with a
reason only for genuinely unit-less code/config/prose.
scope.json: verified, contradicted, not-verifiable-from-diff, or
non-claim. Verified/contradicted claims need citations.
blocking, concern, andnit. 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.
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.
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.
Artifacts are written under the target project:
.techne/review/<slug>/
scope.json # computed by init
review.json # authored by the reviewer
report.json # computed by check
verdict.json # computed by close
Generated .techne/ output belongs to target projects. Do not commit it to this
repository.
Review skeleton:
{
"schema": "techne.vet/1",
"symbols": [
{
"id": "s-...",
"symbol": "changedName",
"disposition": "reviewed",
"refs": [
{
"file": "src/caller.py",
"line": 42,
"effect": "unaffected",
"note": "caller passes the same contract"
}
]
}
],
"hunks": [],
"claims": [
{
"ids": ["c-..."],
"disposition": "verified",
"citations": [{"file": "src/change.py", "line": 10}]
}
],
"findings": [],
"testsAcknowledgment": "No tests changed; the diff is docs-only or existing coverage is enough because ..."
}
Use reference.md for the full JSON schema, rubrics, exclusions, weak spots,
and probe guidance.
base...head diff is available.init refuses because of dirty worktree, missing merge base, or headmismatch; fix the setup or record blocked.
sampling silently.
approve if refs, hunks, claims, or test acknowledgment remainunaccounted.
blocked --reason ... or leave it, then start a new slug for the new head.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
Next.js best practices - file conventions, RSC boundaries, data patterns, async APIs, metadata, error handling, route handlers, image/font optimization, bundling
Take lynxlangya/anchor-vet from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.