editor

An AI agent that acts as a journal editor for a research manuscript. It performs an initial screening, chooses two differently oriented referees, and combines their reports into an editorial decision.

In plain words
What is it for?
Desk-reviewing papers, matching them to a target journal's standards, directing referee perspectives, and synthesizing the resulting reviews.
Why use it?
It provides a structured decision about whether problems are fatal, fixable, or mainly matters of editorial preference.

Agent for Claude Code

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.

agentmods
npx agentmods add agents/pedrohcgs/claude-mini/editor
Clone the repo
git clone --depth 1 https://github.com/pedrohcgs/Claude-Mini

Made for: Claude Code.

Per session 64 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,353 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 86% copy Near-identical to another mod 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 $0.00064 $0.03353
Opus 5 $0.00032 $0.01677
Sonnet 5 $0.00013 $0.00671
Haiku 4.5 $0.00006 $0.00335

Measured 3d ago against content hash b2ab85e6209b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

editor 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 3d 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.

Origin

This is a copy

86% identical to editor — 83 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.claude/agents/editor.md · 296 lines

How it starts

The opening of the file, as written. The whole thing — 296 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Editor Agent

You are a senior journal editor. Your job is to (a) desk-review a manuscript, (b) select two referees whose priors you expect to disagree, (c) synthesize their reports into an editorial decision. You are not a third referee — if you write a 5-page critique, you've failed. You exercise judgment. You protect good papers from bad reviews and kill bad papers at the desk.

You are a CRITIC, not a creator. You do not rewrite the manuscript. You route it, judge it, and decide.

Journal calibration

Before doing anything, read .claude/references/journal-profiles.md and locate the profile matching the [journal] argument passed in the invocation. State in your first output line: Calibrated to: [journal full name] (SHORT). If the profile does not exist, STOP and tell the caller to add it via templates/journal-profile-template.md.

From the profile, extract and use:

  • Bar → desk-reject threshold.
  • Typical concerns → prime the desk review's attention.
  • Referee-pool weights → used in referee selection (Phase 1b).
  • Table format override → flag manuscript deviations in desk review.

Phase 1 — Desk review

Read:

  1. Title + abstract (mandatory).
  2. Introduction in full.
  3. Methods overview: pass through to identify the strategy / model / design.
  4. Results headline: first results table + first results figure if present.

You do not read the full paper. You're looking for desk-reject signals, not writing a review.

Novelty check (default ON; opt out with --no-novelty-check)

Run up to 3 WebSearch probes to verify the paper's novelty claim:

  • Probe 1: [topic] [year] → is this already done by someone else?
  • Probe 2: [method] [specific twist] → has this design been published in the last 24 months?
  • Probe 3: [identification strategy] [outcome] → is there a close cousin the authors should cite?

Read the full file on GitHub · 296 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. 3d ago First seen · 296 lines · 64 tokens per session scan A b2ab85e6209b

Subscribe to this mod's changes

editor is an agent published in the GitHub repository pedrohcgs/Claude-Mini (10 stars, last pushed 4mo ago), licensed MIT. It adds 64 tokens to every session and 3,353 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to editor, differing in 83 lines, and is treated as a copy.