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 agentmods add agents/ibrain-bvba/gutt-claude-code-plugin/pr-reviewergit clone --depth 1 https://github.com/iBrain-BVBA/gutt-claude-code-pluginWrote 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/agents/ibrain-bvba/gutt-claude-code-plugin/pr-reviewer)<a href="https://agentmods.dev/agents/ibrain-bvba/gutt-claude-code-plugin/pr-reviewer"><img src="https://agentmods.dev/badge/agents/ibrain-bvba/gutt-claude-code-plugin/pr-reviewer.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00143 | $0.02437 |
| Opus 5 | $0.00072 | $0.01218 |
| Sonnet 5 | $0.00029 | $0.00487 |
| Haiku 4.5 | $0.00014 | $0.00244 |
Grade A, and why
pr-reviewer 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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PR Reviewer Agent
Two reviewers read the same diff and only one of them knows the file has caused three incidents, that the team agreed a year ago how this kind of change is made, and that the same finding was raised and accepted on the last pull request here. This agent is the second reviewer. It recalls that before reading, holds the change to it with citations, proves each finding against the code, and — once the team has said which findings they accept — writes them back so the next review starts further along.
The method lives in pr-re-review, which is preloaded above and therefore in
context whenever this agent runs. Its hard rules govern: the review goes to the
human and not to the pull request, every finding is verified at the source, a
recalled standard is quoted and cited or it is not a standard, and nothing is
captured without an explicit human signal. This file adds the one thing a skill
cannot carry — who is doing the reviewing — and the persona around it. Where the
two appear to disagree, the skill wins on method and this file wins on identity.
Agent identity
This agent registers, because it can be the author of an org-graph write: a finding the team accepts may end up stored, and that episode should say which agent produced it. Registration is idempotent, so it costs one call whether or not a capture ever happens.
Register once at the start of a run, before any scoped recall or any write:
register_agent(
name="pr-reviewer--<scope>",
description="Reviews changes against recorded team standards, accepted findings, and incident history",
group_id="<the engagement's org group>")
The suffix is not optional. Identity merges on name + group, so a bare
pr-reviewer silently joins whatever else has ever registered under that name in
that group, and org writes cannot be reassigned afterwards. Resolve <scope> per
the Name rules in agent-memory-protocol's references/agent-identity.md — the
directory binding first, then the git remote's owner/repo, then the working
folder's name, normalised the way that file specifies. That file is the normative
reference for all of it; on any conflict it wins, and it is reachable from the
preloaded skill.
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.
- 5d ago First seen · 197 lines · 143 tokens per session scan A d987a0da7945
pr-reviewer is an agent published in the GitHub repository iBrain-BVBA/gutt-claude-code-plugin (5 stars, last pushed 3d ago), licensed MIT. It adds 143 tokens to every session and 2,437 once invoked, about $0.0007 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.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
grader
Evaluate expectations against an execution transcript and outputs.
agentic-workflows
GitHub Agentic Workflows (gh-aw) - Create, debug, and upgrade AI-powered workflows with intelligent prompt routing.