review-orchestrator

review-orchestrator is an agent for Claude Code from OC-NeuralSense/reader-first-writing-skills. It costs 193 tokens per session (1,683 once invoked), scanned A, original, Apache-2.0.

A coordinator for reviewing a document from several separate viewpoints, such as its structure, writing, reasoning, and fit for its readers.

In plain words
What is it for?
It helps organize independent reviews, combine their findings, resolve disagreements, and produce a final assessment.
Why use it?
It prevents a complex review from relying on one person’s perspective or blending all judgments together too early.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter.

Part of the reader-first-writing plugin — 12 skills, 3 agents shipped together

Good fit It helps organize independent reviews, combine their findings, resolve disagreements, and produce a final assessment.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/oc-neuralsense/reader-first-writing-skills/review-orchestrator
Install

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.

Clone the repo
git clone --depth 1 https://github.com/OC-NeuralSense/reader-first-writing-skills

Made for: Claude Code.

Or install reader-first-writing, the plugin that ships this one along with the rest of its 12 skills, 3 agents.

Wrote 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.

agentmods badge for review-orchestrator

README.md
[![agentmods](https://agentmods.dev/badge/agents/oc-neuralsense/reader-first-writing-skills/review-orchestrator/github.svg)](https://agentmods.dev/agents/oc-neuralsense/reader-first-writing-skills/review-orchestrator)
Your own site
<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.

agentmods 80×15 button for review-orchestrator

Your own site · 80×15
<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>
Per session 193 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,683 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 11d ago against content hash f84c045a006a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

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.

agents/review-orchestrator.md · 120 lines

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

  1. The document (proposed output) and its subject reference.
  2. The reader-frame: the shared reader/situation model every reviewer reads from.
  3. The applicable rubric and depth (deep or audit), the genre, and the preservation intent.
  4. Optionally, an argument-blueprint for the document, when the structural review needs it.

What you do

  1. Decompose the review into its lenses: structure, prose, soundness_and_reader_fit.
  2. Spawn one independent-reviewer per 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 single lens. Never pass one reviewer another reviewer's findings, and never pass author rationale, plans, or change history; their reliability depends on that blindness.
  3. Collect the single-lens defect-reports as they return.
  4. 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.
  5. 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.
  6. 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.

Read the full file on GitHub · 120 lines

Changes

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.

  1. 11d ago First seen · 120 lines · 193 tokens per session scan A f84c045a006a

Subscribe to this mod's changes

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.

Related

Other agents, from other repositories

rag-reviewer

Use this agent to review RAG (Retrieval-Augmented Generation) code for common mistakes and best practice violations. Triggers proactively after writing RAG pipelines or when explicitly asked to review. Examples.

Codeblockz/langchain-community-plugin · 44 tokens

langgraph-reviewer

Use this agent to review LangGraph code for common mistakes and best practice violations. Triggers proactively after writing LangGraph code or when explicitly asked to review. Examples.

Codeblockz/langchain-community-plugin · 38 tokens

lean-crew-reviewer

Diff/branch/file reviewer. One line per finding, severity-tagged, no praise, no scope creep. Output format path:line: : . . Use for "review this PR", "review my diff", "audit this file". Skips formatting nits unless they change meaning.

utk2103/Prompt-Studio · 75 tokens

code-reviewer

Code reviewer. Delegate only when the user explicitly starts an Octopus workflow.

nyldn/claude-octopus · 19 tokens

edge-case-explorer

Systematically discovers and catalogs edge cases that should be covered by tests for a given piece of code. Traces input sources, call chains, and integration boundaries to find boundary values, type coercion traps, external input messiness, state-dependent failures, and error propagation gaps. Use when exploring how…

testdouble/han · 135 tokens

feature-reviewer

Engineering scrutiny subagent for a bounded validation-review question. Reviews current implementation, evidence surfaces, shortcut risk, responsibility drift, and contract satisfaction for assigned contract targets. Parent validator decides.

Intelligent-Internet/zenith · 40 tokens