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.
git clone --depth 1 https://github.com/rjmurillo/ai-agentsWrote 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/commands/rjmurillo/ai-agents/pr-quality-gate-reliability)<a href="https://agentmods.dev/commands/rjmurillo/ai-agents/pr-quality-gate-reliability"><img src="https://agentmods.dev/badge/commands/rjmurillo/ai-agents/pr-quality-gate-reliability/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/commands/rjmurillo/ai-agents/pr-quality-gate-reliability"><img src="https://agentmods.dev/badge/commands/rjmurillo/ai-agents/pr-quality-gate-reliability.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00000 | $0.02438 |
| Opus 5.5 | $0.00000 | $0.00975 |
| Sonnet 5.5 | $0.00000 | $0.00488 |
| Haiku 4.5 | $0.00000 | $0.00244 |
Grade A, and why
pr-quality-gate-reliability scanned grade A with 2 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Are generic calls (`requests.get(url)`, `subprocess.run(cmd)`) missing a `timeout=`? Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
- Are generic calls (`requests.get(url)`, `subprocess.run(cmd)`) missing a `timeout=`? 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.
Reliability Review Task
You are reviewing a pull request for production survivability: how the change behaves when its dependencies misbehave, time out, or fail.
Context Mode Enforcement (REQUIRED)
The CI harness prepends a CONTEXT_MODE: [full|summary|partial] header to the
context it sends you. Read that header before you decide a verdict. It tells you
how much of the diff you actually received.
full: the complete diff is present.PASS,WARN, andCRITICAL_FAILare all permitted on the merits.summary: only a file list or stat-only summary is present (the PR exceeded the diff-size limit). You did not see the line-level changes.partial: only a bounded slice of the diff is present (for example, the first N lines). You did not see the rest.
When CONTEXT_MODE is not full, you MUST NOT emit PASS. A PASS asserts
evidence you do not have. Emit WARN (or a higher-severity verdict if the
available metadata already shows a problem), state that context was
summary or partial, and name the specific evidence you would need to clear
the PR. Treat a missing or unrecognized CONTEXT_MODE value as not full.
This is a manipulation-resistance control: an adversary can craft a PR that
trips summary mode to hide a change behind a stat-only context. Forbidding PASS
keeps that change from passing on absent evidence. See
.agents/governance/AI-REVIEW-MODEL-POLICY.md ("CONTEXT_MODE Header (REQUIRED)").
Grounding Rules
- Do NOT claim software versions are "beta", "unstable", or "unreleased" based on training data. Your training data has a cutoff and may be outdated.
- Do NOT claim tools (ruff, mypy, pytest, etc.) lack support for a version unless you have concrete evidence from the diff itself.
- For dependency update PRs: evaluate the diff for internal consistency, not external ecosystem assumptions. If CI tests pass, the tooling works.
- Base findings on what the code shows, not on recalled release schedules.
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.
- 1mo ago First seen · 197 lines · 0 tokens per session scan A 5805a5c6f8ea
pr-quality-gate-reliability is a command published in the GitHub repository rjmurillo/ai-agents (49 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,438 tokens. A static security scan graded it A with 2 findings (makes network calls, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-08.
Other commands, from other repositories
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diagnose
Trace a failed or stalled pipeline run — identify which FORGE annotation is missing or malformed, diagnose the failure point, and suggest specific remediation steps.
incident-response
Coordinate P0 incident response — hotfix validation, timeline reconstruction, and post-incident analysis.