reviewer: Instructions file for Codex

AGENTS.md

reviewer AGENTS.md is an instructions file for Codex, OpenCode from Ingar30/reviewer. It costs 1,468 tokens per session, scanned A, original, MIT.

Instructions for a reproducible system that uses several software agents to review academic economics papers. It processes research PDFs, assigns reviewers, validates their structured results, and combines them for editing.

In plain words
What is it for?
Use it to preprocess papers, check parser quality, choose reviewers, run reviews, validate JSON results, remove duplicate findings, and prepare material for an editor.
Why use it?
It defines where each paper artifact belongs and which checks happen before review, reducing confusion and inconsistent results across review runs. It also records reviewer selection and output validation for later inspection.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions Claude Code; mentions AGENTS.md; mentions Codex.

This is Ingar30/reviewer's own configuration. It tells Codex and OpenCode how to work on reviewer itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything reviewer configures →

Reuse

Borrowing it

Nothing to install: this file belongs to Ingar30/reviewer. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/Ingar30/reviewer/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/Ingar30/reviewer

Made for: Codex, OpenCode.

Wrote this? Show the measurements

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Per session 1,468 This file is loaded in full into every session.
When invoked 1,468 The same file — it is already loaded in full.
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 $0.01468 $0.01468
Opus 5.5 $0.00587 $0.00587
Sonnet 5.5 $0.00294 $0.00294
Haiku 4.5 $0.00147 $0.00147

Measured 14d ago against content hash 493078b376ff, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

reviewer AGENTS.md 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 14d 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.md · 74 lines

How it starts

The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

Project purpose

This repository builds and runs a reproducible multi-agent reviewer for academic economics papers.

The normal workflow is:

  1. Put source PDFs in inputs/.
  2. Preprocess each paper into structured artifacts under work/<paper_id>/parsed/.
  3. Render run-specific prompts under work/<paper_id>/prompts/.
  4. Run parser-quality preflight before substantive review.
  5. Route substantive reviewers around parser-quality warnings using deterministic artifacts.
  6. Run the single conservative applicability router. The 8 universal review-stage auditors always run; conditional specialists are skipped only when their entire remit is clearly absent. Mixed, unknown, or lower-confidence classifications expand to every conditional specialist.
  7. Store applicability provenance and the active reviewer roster under work/<paper_id>/selection/.
  8. Rerender prompts for the selected reviewer roster with parser-quality guidance.
  9. Run the selected reviewer agents on the parsed artifacts.
  10. Store and validate reviewer JSON outputs under work/<paper_id>/reviews/.
  11. Conservatively normalize reviewer outputs into a precision-first, lossless editor bundle that preserves every source finding's details and avoids merging distinct concerns.
  12. Build editor input from a deterministic brief, the lossless normalized bundle, and a compact provenance index for the validated reviewer JSON files. Do not duplicate raw reviewer JSON or truncate evidence.
  13. Run the editor to author structured editorial decisions/prose, then validate and deterministically render the final Markdown under outputs/<paper_id>/report.md.
  14. Smoke-check the final report.

Canonical file locations

  • Source PDFs: inputs/
  • Parsed artifacts: work/<paper_id>/parsed/
  • Reviewer outputs: work/<paper_id>/reviews/
  • Reviewer selection: work/<paper_id>/selection/
  • Final reports: outputs/<paper_id>/

Path conventions

  • If the user refers to a bare source PDF filename, first resolve it under inputs/.
  • Prefer project-relative paths over absolute paths when possible.
  • Do not assume a file is outside the repo unless the user explicitly says so.

Read the full file on GitHub · 74 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. 14d ago Changed · +23 tokens per session 493078b376ff
  2. 1mo ago Changed · +62 tokens per session f2dd2f199872
  3. 1mo ago Changed · +1 lines · +78 tokens per session 4b16e66e1ab0
  4. 1mo ago Changed · +81 tokens per session 702e0e15b7c3
  5. 1mo ago Changed · +7 lines · +185 tokens per session 16a50c9e7cf0
  6. 2mo ago Changed · +1 lines · +187 tokens per session 2497229e96f8
  7. 2mo ago First seen · 65 lines · 852 tokens per session scan A 46a9b6700a4a

Subscribe to this mod's changes

reviewer AGENTS.md is an instructions file published in the GitHub repository Ingar30/reviewer (230 stars, last pushed 8d ago), licensed MIT. It adds 1,468 tokens to every session, about $0.0059 per session on Opus 5.5. 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 2026-08-30.

Related

reviewer AGENTS.md compared with instructions from other repositories

reviewer AGENTS.md next to 6 instructions from other repositories
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reviewer AGENTS.mdIngar30/reviewerInstructions file2308d agoMITA1,468Codex, OpenCode
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deepseek-harness AGENTS.mddeepseek-ai/deepseek-harnessInstructions file274k2d agoMITA4,313Codex, OpenCode