Borrowing it
Nothing to install: this file belongs to warpdotdev/oz-for-oss. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/warpdotdev/oz-for-oss/main/.agents/skills/review-spec-local/SKILL.mdgit clone --depth 1 https://github.com/warpdotdev/oz-for-ossWrote 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.
[](https://agentmods.dev/skills/warpdotdev/oz-for-oss/review-spec-local)<a href="https://agentmods.dev/skills/warpdotdev/oz-for-oss/review-spec-local"><img src="https://agentmods.dev/badge/skills/warpdotdev/oz-for-oss/review-spec-local.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00032 | $0.00298 |
| Opus 5 | $0.00016 | $0.00149 |
| Sonnet 5 | $0.00006 | $0.00060 |
| Haiku 4.5 | $0.00003 | $0.00030 |
Grade A, and why
review-spec-local 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 8d ago.
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.
What it actually says
Repo-specific spec-review guidance for oz-for-oss
This file is a companion to the core review-spec skill. It does not
redefine the review output schema, severity labels, safety rules, or
evidence rules. It only specializes the override categories the core
skill marks as overridable.
Required spec sections in this repository
Spec pull requests in this repo land under specs/GH<issue-number>/ and
typically include both a product.md and a tech.md. When reviewing, check that:
product.mdclearly states the problem, goals, non-goals, user experience, and validation plantech.mdclearly states the problem, relevant code, current state, proposed changes, risks, and follow-ups- both files reference the originating GitHub issue by number in the top-level heading
- internal links reference files and line ranges using the repo-root-relative convention (for example
path/file:lineorpath/file (start-end))
Linking conventions
- Prefer repo-root-relative links over absolute filesystem paths in spec prose.
- When a spec references another spec in the same repository, link to it via its relative path under
specs/.
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.
- 8d ago First seen · 28 lines · 32 tokens per session scan A 4eb16e580c6e
review-spec-local is a skill published in the GitHub repository warpdotdev/oz-for-oss (307 stars, last pushed 6d ago), licensed MIT. It adds 32 tokens to every session and 298 once invoked, about $0.0002 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…