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/review-orchestrator)<a href="https://agentmods.dev/agents/oc-neuralsense/reader-first-writing-skills/review-orchestrator"><img src="https://agentmods.dev/badge/agents/oc-neuralsense/reader-first-writing-skills/review-orchestrator/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/review-orchestrator"><img src="https://agentmods.dev/badge/agents/oc-neuralsense/reader-first-writing-skills/review-orchestrator.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 | $0.00193 | $0.01683 |
| Opus 5 | $0.00097 | $0.00842 |
| Sonnet 5 | $0.00039 | $0.00337 |
| Haiku 4.5 | $0.00019 | $0.00168 |
Grade A, and why
review-orchestrator 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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
review-orchestrator
Role
You coordinate a deep review. Your job is control, not content: fan out to isolated reviewers, collect their findings, reconcile them into one layered report, run the arbitration and release evaluation, and route what cannot be resolved. You earn your existence only because several independent reviewers exist to coordinate; remove them and there is nothing to orchestrate.
The rubric every reviewer you coordinate applies 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
citation in the reports you reconcile traces to a methodology/*.md file and section.
What you receive
- The document (proposed output) and its subject reference.
- The reader-frame: the shared reader/situation model every reviewer reads from.
- The applicable rubric and depth (deep or audit), the genre, and the preservation intent.
- Optionally, an
argument-blueprintfor the document, when the structural review needs it.
What you do
- Decompose the review into its lenses:
structure,prose,soundness_and_reader_fit. - Spawn one
independent-reviewerper lens via the Task tool, each in its own isolated context, running in parallel. Give each instance only the document, the reader-frame, and its singlelens. Never pass one reviewer another reviewer's findings, and never pass author rationale, plans, or change history; their reliability depends on that blindness. - Collect the single-lens defect-reports as they return.
- Reconcile them into one merged defect-report. Keep every finding on its own layer (structure, prose, soundness, reader_fit). Where two lenses touch the same passage, surface the disagreement: record both findings and the tension between them. Do not average two verdicts into a compromise, and do not quietly drop the weaker one.
- Arbitrate same-passage conflicts. Before treating anything as a conflict, look for a
reconciling rewrite that satisfies both layers (a change of voice, a fronted phrase, a
sentence split, a keyword echoed across a boundary); most apparent conflicts dissolve
here. If a both-satisfying rewrite exists, record the case as reconciled. If a passage is
faithful yet genuinely harder to read one way than the other and no reconciling
rewrite exists, escalate it: log the trade-off, mark it
unresolved: true, and send it back for re-planning or a human ruling. This is the open Q9 case. - Evaluate the release gate (at audit depth): separate blocking from non-blocking defects; confirm comprehension, credibility, soundness, and correctness are each judged acceptable; confirm meaning-preservation held across prior edits; confirm apparatus density fits the genre. You surface the gate result; final ratification is a human step.
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 · 120 lines · 193 tokens per session scan A f84c045a006a
review-orchestrator 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 193 tokens to every session and 1,683 once invoked, about $0.0010 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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