dual-ai-paper-coach: Command for Claude Code

.claude/commands/claim-check.md

claim-check is a command for Claude Code, Codex from dengxu11111/dual-ai-paper-coach. It costs 21 tokens per session (1,577 once invoked), scanned A, original, MIT.

A workflow for comparing how Claude and Codex judge the credibility and wording of a research paper’s main claims. A claim is a specific statement the paper says its evidence supports.

In plain words
What is it for?
Use it to extract key claims, score their evidence and wording, compare the two assessments, and focus revisions on the largest disagreements.
Why use it?
It highlights claims where the two AI reviewers disagree, helping identify conclusions that may be weakly supported or stated too strongly.

Command for Claude CodeCodex

Written for Claude Code and Codex: installed under .claude/, but also runs codex exec. Also seen: mentions AGENTS.md; mentions Codex.

This is dengxu11111/dual-ai-paper-coach's own configuration. It tells Claude Code and Codex how to work on dual-ai-paper-coach 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 dual-ai-paper-coach configures →

Reuse

Borrowing it

Nothing to install: this file belongs to dengxu11111/dual-ai-paper-coach. 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/dengxu11111/dual-ai-paper-coach/main/.claude/commands/claim-check.md
Clone the repo
git clone --depth 1 https://github.com/dengxu11111/dual-ai-paper-coach

Made for: Claude Code, Codex.

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 claim-check

README.md
[![agentmods](https://agentmods.dev/badge/commands/dengxu11111/dual-ai-paper-coach/claim-check/github.svg)](https://agentmods.dev/commands/dengxu11111/dual-ai-paper-coach/claim-check)
Your own site
<a href="https://agentmods.dev/commands/dengxu11111/dual-ai-paper-coach/claim-check"><img src="https://agentmods.dev/badge/commands/dengxu11111/dual-ai-paper-coach/claim-check/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 claim-check

Your own site · 80×15
<a href="https://agentmods.dev/commands/dengxu11111/dual-ai-paper-coach/claim-check"><img src="https://agentmods.dev/badge/commands/dengxu11111/dual-ai-paper-coach/claim-check.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 21 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,577 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 $0.00021 $0.01577
Opus 5 $0.00010 $0.00788
Sonnet 5 $0.00004 $0.00315
Haiku 4.5 $0.00002 $0.00158

Measured 12d ago against content hash 4f3c843c13c2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

claim-check 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 12d 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.

.claude/commands/claim-check.md · 124 lines

How it starts

The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/claim-check — 双 AI Claim 校准

Claude 和 Codex 独立给论文 1-3 个核心 claim 打分,分歧 ≥ 20 的就是论文最脆的地方。

⚠️ 打分标杆:Science / Nature——Codex 按 S/N 审稿人的怀疑度打 evidence;S/N 标杆下 evidence ≥ 80 才算"经得起多学科读者审视"。Codex 打分偏低是设计上的特性。

步骤

步骤 1:提取 claims

my-paper/draft.md 的 Abstract,把 1-3 句"主张"提取成 YAML:

# my-paper/claims.yaml
claims:
  - id: C1
    text: "Global AOD declined 10% over 2010-2024"
    section: Results §3.1
    evidence_keys: [global_mean.trend_per_decade]
  - id: C2
    text: "Decline driven by East Asia anthropogenic reduction"
    section: Discussion §4.2
    evidence_keys: [regional_trends.east_asia]
  - id: C3
    text: "Aerosol policy has improved global air quality"
    section: Conclusions §5
    evidence_keys: []   # 推论性 claim,最容易被打低分

如果 claims.yaml 已存在,直接用现有的;否则你(Claude)提取并写入。

步骤 2:Claude 自评(你来做)

prompts/writer_system.md不要读 reviewer_system.md。基于 draft + analysis_results.json,给每个 claim 打两个维度:

  • evidence(0-100):数据支持度
  • wording(0-100):当前措辞强度(>80 = overclaim)

输出 JSON 到 my-paper/runs/<ts>/claim_score_claude.json

{
  "C1": {"evidence": 85, "wording": 80, "reason_evidence": "...", "reason_wording": "..."},
  "C2": {"evidence": 75, "wording": 85, "reason_evidence": "...", "reason_wording": "..."},
  "C3": {"evidence": 60, "wording": 70, "reason_evidence": "...", "reason_wording": "..."}
}

步骤 3:Codex 自评(通过 Bash 触发)

codex exec --skip-git-repo-check --sandbox workspace-write \
  -c 'model_reasoning_effort="xhigh"' \
  "Read AGENTS.md, my-paper/draft.md, my-paper/claims.yaml, and my-paper/data/analysis_results.json. Apply Science/Nature reviewer standards: a multidisciplinary PhD reader must find the evidence convincing. For each claim, score evidence (0-100; how strongly the data + reported statistics support the claim at S/N standard) and wording (0-100; >80 = overclaim that S/N reviewers would reject). Output JSON to my-paper/runs/<ts>/claim_score_codex.json."

关键参数(与 /codex-review 同源):

  • --sandbox workspace-write 必须——Codex 默认沙盒只读,写不进 JSON
  • -c 'model_reasoning_effort="xhigh"' 审稿用 xhigh,默认 medium 不够严

Read the full file on GitHub · 124 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. 12d ago First seen · 124 lines · 21 tokens per session scan A 4f3c843c13c2

Subscribe to this mod's changes

claim-check is a command published in the GitHub repository dengxu11111/dual-ai-paper-coach (12 stars, last pushed 4mo ago), licensed MIT. It adds 21 tokens to every session and 1,577 once invoked, about $0.0001 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 2026-08-30.