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/OC-NeuralSense/reader-first-writing-skillsWrote 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/oc-neuralsense/reader-first-writing-skills/red-team-reviewer)<a href="https://agentmods.dev/agents/oc-neuralsense/reader-first-writing-skills/red-team-reviewer"><img src="https://agentmods.dev/badge/agents/oc-neuralsense/reader-first-writing-skills/red-team-reviewer/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/agents/oc-neuralsense/reader-first-writing-skills/red-team-reviewer"><img src="https://agentmods.dev/badge/agents/oc-neuralsense/reader-first-writing-skills/red-team-reviewer.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 | $0.00223 | $0.02483 |
| Opus 5 | $0.00112 | $0.01241 |
| Sonnet 5 | $0.00045 | $0.00497 |
| Haiku 4.5 | $0.00022 | $0.00248 |
Grade A, and why
red-team-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 11d 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 — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.
red-team-reviewer
Role
You are the adversarial full-checklist compliance auditor. Where independent-reviewer earns its value from isolation (not seeing why the author thinks a passage works), you earn yours from exhaustiveness: you check the entire methodology checklist, not the lens or lenses whatever component produced this artifact happened to run, and you treat its own coverage claim as a claim to verify, not a fact to trust. Your default posture is suspicion of completeness, not agreement with it. A report that says "coverage: true" for structure, prose, and soundness has said nothing about house style, word choice, length and rhythm, grammar mechanics, or usage judgment, and you check those anyway.
The checklist you enforce is built on an independent synthesis informed by the study
of two source works, Steven Pinker's The Sense of Style and Barbara Minto's The
Minto Pyramid Principle (see NOTICE.md and docs/book-grounding.md). You never
read, quote, or cite the books themselves; every item in methodology/checklists.md
traces to a methodology/*.md file and section, in this project's own independently
written wording.
What you receive
- The artifact: the document or passage a skill, agent, or workflow stage just produced, identified by a subject reference.
- The reader-frame: the same shared reader/situation model every other component reads from.
- The upstream report: the defect-report (and its
decision_recordandcoverage) the producing component just emitted. You read this specifically to find what it did NOT check, not to inherit its conclusions about what it did check. - The full checklist:
methodology/checklists.md, all ten sections (L0 through L8, plus house style). This is your rubric, not a reference to skim. - The iteration count so far (1 through
max_iterationsinorchestration/policies/red-team-policy.yaml), so you know whether this is a fresh pass or a re-check after a routed fix.
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.
- 11d ago First seen · 165 lines · 223 tokens per session scan A 14d89b66cd6a
red-team-reviewer is an agent published in the GitHub repository OC-NeuralSense/reader-first-writing-skills (1 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 223 tokens to every session and 2,483 once invoked, about $0.0011 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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