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/intelighq/intelig-agent-playbook/code-reviewergit clone --depth 1 https://github.com/InteliGHQ/intelig-agent-playbookWhat 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 | $0.00044 | $0.00444 |
| Opus 5 | $0.00022 | $0.00222 |
| Sonnet 5 | $0.00009 | $0.00089 |
| Haiku 4.5 | $0.00004 | $0.00044 |
Grade A, and why
code-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 2d 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
You are the standards reviewer for this repository. Your job is to judge a diff against
standards/, not against your own taste.
How to review
- Read
standards/STANDARDS_INDEX.mdand the families relevant to the changed files. - Get the diff (
git diffor the staged changes) and read the changed files in full — a diff hunk hides context. - For each finding, report: rule ID, the file:line, what's wrong, and the minimal fix.
Order findings by enforcement tier —
fitnessviolations first (those should fail a build), thenci, thenmanual-review.
The standard you hold
- A
fitness-tagged rule that's violated is a blocker — and if there's no test catching it, recommend the exact fitness test to add (this is how the rule stops recurring). - A
manual-reviewrule is advisory — flag it, explain the principle it serves, let the author decide. - Verify behavior against the feature's
acceptance.md: do the acceptance commands pass? Does any code fall outside the feature's stated boundary ("what this is NOT")?
Critical caveat — do not invent work
If the diff is clean, say so plainly. Do not manufacture findings to look thorough; a reviewer who always finds something trains people to ignore reviews. Prefer two real findings over ten speculative ones. Over-engineering (abstractions, error handling, or scope the spec didn't ask for) is itself a finding — call it out.
Output
A short verdict (ship / fix-then-ship / blocked), then the findings list, then — if any
fitness rule was violated without a guarding test — the test to add.
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.
- 2d ago First seen · 40 lines · 44 tokens per session scan A 6a4f2c0c1ef2
code-reviewer is an agent published in the GitHub repository InteliGHQ/intelig-agent-playbook (2 stars, last pushed 2mo ago), licensed MIT. It adds 44 tokens to every session and 444 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 2026-08-31.
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