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.
npx skills add in-the-loop-labs/pair-review --skill user-criticgit clone --depth 1 https://github.com/in-the-loop-labs/pair-reviewWrote 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/in-the-loop-labs/pair-review/user-critic)<a href="https://agentmods.dev/skills/in-the-loop-labs/pair-review/user-critic"><img src="https://agentmods.dev/badge/skills/in-the-loop-labs/pair-review/user-critic/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.
<a href="https://agentmods.dev/skills/in-the-loop-labs/pair-review/user-critic"><img src="https://agentmods.dev/badge/skills/in-the-loop-labs/pair-review/user-critic.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00056 | $0.00351 |
| Opus 5 | $0.00028 | $0.00176 |
| Sonnet 5 | $0.00011 | $0.00070 |
| Haiku 4.5 | $0.00006 | $0.00035 |
Grade A, and why
user-critic 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.
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
Address Review Feedback
Fetch human-curated review comments from pair-review and make code changes to address each one.
Determine review context
Determine whether this is a local review or a PR review:
- If the user explicitly says "local", use local mode.
- Otherwise, determine the GitHub owner, repo, and PR number for the current branch. If a PR exists, use PR mode with
repoandprNumberparams. - If no PR exists, use local mode with
path(absolute cwd) andheadSha(git rev-parse HEAD) params.
Fetch comments
Call mcp__pair-review__get_user_comments with the review context params.
If no comments are returned, tell the user there's nothing to address.
Address each comment
For each comment returned:
- Read the file at the referenced path and lines.
- Understand what the reviewer is asking for — it may be a bug fix, a refactoring request, a question, or a style change.
- Make the code change that addresses the feedback.
- If the comment is a question or unclear, explain your interpretation and what you changed.
Report
After addressing all comments, provide a summary:
- Which files were changed
- What was done for each comment
- Any comments that were ambiguous or could not be addressed (explain why)
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 · 42 lines · 56 tokens per session scan A 31354500627c
user-critic is a skill published in the GitHub repository in-the-loop-labs/pair-review (58 stars, last pushed today), licensed Apache-2.0. It adds 56 tokens to every session and 351 once invoked, about $0.0003 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.
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