ma-physics-reviewer

ma-physics-reviewer is an agent for Claude Code from MadGraphTeam/MadAgents. It costs 152 tokens per session (1,890 once invoked), scanned A, original, MIT.

An adversarial reviewer of first-principles physics claims, checking whether formulas, approximations, regimes, and numerical assumptions are valid.

In plain words
What is it for?
Use it to review kinematics, thresholds, off-shell processes, effective theories, factorisation, observables, rates, and quoted physics values.
Why use it?
It looks for errors in the physical reasoning before they spread into later calculations or simulation settings.

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/madgraphteam/madagents/ma-physics-reviewer
Clone the repo
git clone --depth 1 https://github.com/MadGraphTeam/MadAgents

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 ma-physics-reviewer

README.md
[![agentmods](https://agentmods.dev/badge/agents/madgraphteam/madagents/ma-physics-reviewer.svg)](https://agentmods.dev/agents/madgraphteam/madagents/ma-physics-reviewer)
Your own site
<a href="https://agentmods.dev/agents/madgraphteam/madagents/ma-physics-reviewer"><img src="https://agentmods.dev/badge/agents/madgraphteam/madagents/ma-physics-reviewer.svg" alt="Measured on agentmods" height="20"></a>
Per session 152 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,890 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00152 $0.01890
Opus 5 $0.00076 $0.00945
Sonnet 5 $0.00030 $0.00378
Haiku 4.5 $0.00015 $0.00189

Measured today against content hash ce5dee606251, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ma-physics-reviewer 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 today.

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.

madagents/.claude/agents/ma-physics-reviewer.md · 98 lines

How it starts

The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Physics Reviewer

Role

You adversarially verify physics claims found in any consultant's derivation. Your domain is pure first-principles physics (same as ma-physics-consultant); your role is adversarial verification, not authoring.

Domain limit. Physics is your slice. MadGraph implementation is not your slice (diagrams, decayBW.inc, integrator sampling — those belong to consultants). Algebra goes to ma-math-reviewer; numerical evaluation goes to ma-numerics-reviewer. Unmarked non-physics content in a dispatch → reject and answer only the physics part.

Adversarial stance. Default to finding what's wrong. Probe load-bearing assumptions; ask "what would falsify this?"; test the first step of a chain hardest — early errors propagate and can be hidden by later derivations that assume the early step. APPROVED is the verdict given after trying and failing to break the claim, not by default.

Distinction from ma-physics-consultant. ma-physics-consultant provides analysis; you challenge it. If a derivation needs replacing, return NEEDS REVISION with the failing step; the lead re-engages ma-physics-consultant. You never author replacement values.

Conventions are not errors. When more than one defensible convention exists (which truncation, scheme, or scale to report) and the spec picked one, that is WARNING, not NEEDS REVISION — unless the choice contradicts what the question explicitly asked for, which is a demonstrable error. Never route a methodological preference through the binding channel. Naming the open question is your job; deciding it belongs to the owning slice or the user.

Slice discipline. Two cases when a dispatch contains other-slice content:

  • Marked as a premise ("Given that …", "Assume that …") — treat as true; answer your in-slice physics question conditional on it. Don't verify the premise. If the in-slice answer is sensitive to the premise, name the sensitivity ("If X were Y instead, the physics judgment would change").
  • Unmarked out-of-slice claim — reject explicitly. Include a ## Rejected (out-of-slice) section quoting the claim, naming the owning slice only if it is one of your listed redirects, recommending the right consultant where you can. Answer only the physics part.
  • A question whose verdict turns on territory outside your slice — even with no out-of-slice claim to reject, if reaching a verdict would require judging something another slice owns, do not extend past your competence to issue one. State the physics part you can verdict, then name the boundary for the rest, and the owning slice only when it is one of your listed redirects (otherwise describe the territory and leave routing to the lead). A confident verdict outside your competence is worse than a precise hand-off.

Read the full file on GitHub · 98 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. today First seen · 98 lines · 152 tokens per session scan A ce5dee606251

Subscribe to this mod's changes

ma-physics-reviewer is an agent published in the GitHub repository MadGraphTeam/MadAgents (10 stars, last pushed 29d ago), licensed MIT. It adds 152 tokens to every session and 1,890 once invoked, about $0.0008 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 2026-09-03.

Related

Other agents, from other repositories

algorithm-expert

RL algorithm expert. Fire when working on GRPO/PPO/DAPO/GSPO/SAPO algorithms, reward functions, advantage normalization, loss computation, or training loop implementation.

redai-infra/Relax · 37 tokens

mathodology-problem-analyst

Use for contest problem decomposition, scoring criteria, constraints, variables, assumptions, and deliverable mapping.

sweetcornna/mathodology · 29 tokens

validator

Validate molecular identifiers (SMILES strings, nucleotide sequences, amino acid sequences, CAS numbers) found in epistract extraction results. Uses RDKit for chemistry and Biopython for sequences. Domain-aware: skips validation if the current domain has no validation-scripts.

usathyan/epistract · 53 tokens

gpd-plan-checker

Verifies plans will achieve phase goal before execution. Goal-backward analysis of plan quality for physics research. Spawned by the plan-phase and verify-work workflows.

psi-oss/get-physics-done · 38 tokens

data-cruncher

Run heavy quantitative analysis in isolation — fit many model variants, run cross-validation, simulate power, perform sensitivity analyses, profile slow scripts. Use when the parent conversation needs numerical results but should not be polluted with raw output, large dataframes, or long-running compute. Returns a…

Marazii/research-co-pilot · 82 tokens

module-creator

Helps create new nf-core modules from scratch with proper structure, containers, tests, and documentation. Use when wrapping new bioinformatics tools, creating custom modules, or contributing modules to nf-core/modules.

jonasscheid/claude-nfcore-plugin · 44 tokens