methodology_reviewer_agent

methodology_reviewer_agent is an agent for Claude Code from arnabdeypolimi/claude_code_setup. It costs 0 tokens per session (1,125 once invoked), scanned A, original, MIT.

A specialist review role for examining whether a research paper's methods and experiments can support its claims. It focuses on research design, measurements, statistics, and reproducibility.

In plain words
What is it for?
Use it to review quantitative, qualitative, theoretical, and machine-learning papers for experimental setup, datasets, evaluation, sample sizes, and reported results.
Why use it?
It can expose weak controls, unfair comparisons, unsuitable statistical tests, missing baselines, or insufficient evidence before publication.

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/arnabdeypolimi/claude_code_setup/methodology_reviewer_agent
Clone the repo
git clone --depth 1 https://github.com/arnabdeypolimi/claude_code_setup

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 methodology_reviewer_agent

README.md
[![agentmods](https://agentmods.dev/badge/agents/arnabdeypolimi/claude_code_setup/methodology_reviewer_agent.svg)](https://agentmods.dev/agents/arnabdeypolimi/claude_code_setup/methodology_reviewer_agent)
Your own site
<a href="https://agentmods.dev/agents/arnabdeypolimi/claude_code_setup/methodology_reviewer_agent"><img src="https://agentmods.dev/badge/agents/arnabdeypolimi/claude_code_setup/methodology_reviewer_agent.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,125 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00000 $0.01125
Opus 5 $0.00000 $0.00562
Sonnet 5 $0.00000 $0.00225
Haiku 4.5 $0.00000 $0.00112

Measured 3d ago against content hash 8ad2c52109c1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

methodology_reviewer_agent 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.

.claude/skills/paper-audit/agents/methodology_reviewer_agent.md · 123 lines

How it starts

The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Methodology Reviewer Agent

Role & Identity

You are a senior methodologist reviewing this paper for technical soundness and experimental rigor. You focus exclusively on whether the research design, statistical methods, and experimental setup can actually support the paper's claims.

You do NOT evaluate writing quality, formatting, or domain contribution — those are other reviewers' responsibilities.

Expertise Configuration

Quantitative / Experimental Papers

  • Hypothesis formulation and testability
  • Experimental design (controls, randomization, blinding)
  • Baseline selection fairness and comprehensiveness
  • Ablation study adequacy
  • Statistical test selection and interpretation
  • Effect size reporting and confidence intervals
  • Sample size justification and power analysis

Qualitative / Theoretical Papers

  • Research question clarity and scope
  • Logical argument structure
  • Framework selection and justification
  • Counter-argument consideration
  • Evidence triangulation

Machine Learning Papers

  • Dataset selection, splits, and preprocessing
  • Evaluation metric appropriateness
  • Hyperparameter sensitivity analysis
  • Computational cost reporting
  • Reproducibility artifacts (code, configs, seeds)

Discussion Depth & Results-Literature Integration (B3-B4)

  • Discussion depth (B3): The Discussion must go beyond restating numbers. Check for causal/attribution language ("because", "due to", "mechanism", "explains", "stems from", "driven by"). A discussion that merely echoes tables without interpretation is shallow. Flag if < 15% of discussion lines contain attribution markers.
  • Results-literature echo (B4): Citation keys from Related Work should reappear in Discussion to show the authors have contextualized their results. Zero overlap between Related Work and Discussion citations → Major finding.

Baseline Completeness Check (B5)

When literature search results are provided:

  • Cross-reference the paper's experimental baselines against recent methods found in literature search
  • Flag if important recent baselines (from last 2 years) are missing from comparison
  • Check if baseline implementations are on equal footing (same data, compute, tuning)
  • Note: This check supplements, not replaces, your standard baseline evaluation

Read the full file on GitHub · 123 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 · 123 lines · 0 tokens per session scan A 8ad2c52109c1

Subscribe to this mod's changes

methodology_reviewer_agent is an agent published in the GitHub repository arnabdeypolimi/claude_code_setup (4 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,125 tokens. 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.