baseline-comparison-audit

baseline-comparison-audit is a skill for Claude Code from wanshuiyin/Anti-Autoresearch. It costs 310 tokens per session (15,911 once invoked), scanned A, original, MIT.

A research-paper audit for checking whether comparisons with other methods are complete, fair, and meaningful.

In plain words
What is it for?
Use it to inspect claims that a paper is state of the art, compare the resources given to each method, and produce evidence-linked audit findings.
Why use it?
It identifies missing recent state-of-the-art methods, unfairly tuned comparison methods, mismatched settings, and missing equal-resource tests before a final verdict is made.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: mentions Codex.

Good fit Use it to inspect claims that a paper is state of the art, compare the resources given to each method, and produce evidence-linked audit findings.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/wanshuiyin/anti-autoresearch/baseline-comparison-audit
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.

Any agent
npx skills add wanshuiyin/Anti-Autoresearch --skill baseline-comparison-audit
Clone the repo
git clone --depth 1 https://github.com/wanshuiyin/Anti-Autoresearch

Made for: Claude Code.

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 baseline-comparison-audit

README.md
[![agentmods](https://agentmods.dev/badge/skills/wanshuiyin/anti-autoresearch/baseline-comparison-audit/github.svg)](https://agentmods.dev/skills/wanshuiyin/anti-autoresearch/baseline-comparison-audit)
Your own site
<a href="https://agentmods.dev/skills/wanshuiyin/anti-autoresearch/baseline-comparison-audit"><img src="https://agentmods.dev/badge/skills/wanshuiyin/anti-autoresearch/baseline-comparison-audit/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 baseline-comparison-audit

Your own site · 80×15
<a href="https://agentmods.dev/skills/wanshuiyin/anti-autoresearch/baseline-comparison-audit"><img src="https://agentmods.dev/badge/skills/wanshuiyin/anti-autoresearch/baseline-comparison-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 310 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 15,911 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. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 2 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Anti-Refusal · line 354
    Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.
    Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
  • high Anti-Refusal · line 475
    Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.
    Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
How audits are shown
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 $0.00310 $0.15911
Opus 5 $0.00155 $0.07956
Sonnet 5 $0.00062 $0.03182
Haiku 4.5 $0.00031 $0.01591

Measured 13d ago against content hash d706bd83830c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

baseline-comparison-audit 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 13d 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

Copies of this mod

1 near-identical copy found in the catalogue:

skills/baseline-comparison-audit/SKILL.md · 947 lines

How it starts

The opening of the file, as written. The whole thing — 947 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Baseline Comparison Audit — is the comparison complete, fair, and significant?

Audit baseline-comparison integrity for: $ARGUMENTS (requires claims.json from /evidence-ledger). Emit span-anchored baseline-comparison-audit.findings.json. This skill computes no verdict.

🔒 Do not wrap this skill in /loop, /schedule, or CronCreate. It is verdict-bearing input — it proposes the findings the deterministic adjudicator turns into the report. Re-firing it on a wall-clock timer adds no signal: its output changes only when the paper / ledger (or the live leaderboard it cross-checks) changes, not with the clock. Schedule the external wait that precedes it — ledger built → audit once. (Mirrors ARIS's external-cadence doctrine.)

Adapted from ARIS paper-claim-audit — its scope-overclaim and delta-arithmetic checks, reframed from "paper vs result files" to "is the SOTA claim earned, and is the comparison a fair fight?" — plus a per-domain baseline profile and a completeness / fairness / significance split. A favourite autoresearch shortcut is to claim SOTA while omitting the obvious recent baseline, to beat an undertuned one, or to write "outperforms" over error bars that overlap. This skill is the constraint that asks for the fair fight, pointed at a third party's submission, and it stays honest about what it cannot settle from a PDF.

Why this exists

An autoresearch pipeline (or rushed human) optimises for the headline and treats the comparison table as scaffolding to fill, not a fair experiment to run. The repeatable failure modes:

  • Completeness — "achieves state-of-the-art on GSM8K" while the obvious recent baseline a 2024–2026 reviewer expects is simply absent from the table, or the strong classical floor (BM25 for retrieval, GBDT for tabular, a linear/naive forecaster for time-series) is skipped while only weak neural baselines are beaten. HP-MISSING-BASELINE
  • Fairness — the proposed method is tuned for 100 epochs / 5 seeds / extra data, the baseline is run at default settings for 10; or the compared rows use different backbones, splits, or eval protocols; or the single most informative baseline — the method's own backbone with the new component removed, at an identical budget — is missing. HP-WEAK-BASELINE
  • Significance — "consistently outperforms" on a 0.3-point gap with overlapping error bars, with no variance / no seed count reported at all, or resting on a single dataset too thin for the "consistent / across-the-board" wording. HP-SIG-OVERLAP
  • Delta arithmetic — "improves over the strongest baseline by 16%" when the baseline row is 73.1 and the proposed row is 78.0 (+6.7% relative / +4.9 points), the two operands sitting in different cells so the single-sentence deterministic pass cannot pair them. HP-DELTA-ERROR (cross-row form)

Read the full file on GitHub · 947 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. 13d ago First seen · 947 lines · 310 tokens per session scan A d706bd83830c

Subscribe to this mod's changes

baseline-comparison-audit is a skill published in the GitHub repository wanshuiyin/Anti-Autoresearch (153 stars, last pushed 3d ago), licensed MIT. It adds 310 tokens to every session and 15,911 once invoked, about $0.0015 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.

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