cross-validate

cross-validate is a skill for Claude Code from Mexregkan/claude-for-researchers. It costs 36 tokens per session (834 once invoked), scanned A, original, MIT.

A command that prepares a result, calculation, or derivation so another AI model can check it independently.

In plain words
What is it for?
Use it to validate a precise formula or claim by stating its notation, inputs, assumptions, and valid range in a form suitable for cross-checking.
Why use it?
A second model may catch errors that the first model missed, especially in physics or mathematics. Disagreement shows which part needs closer review.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: mentions Gemini CLI.

Good fit Use it to validate a precise formula or claim by stating its notation, inputs, assumptions, and valid range in a form suitable for cross-checking.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/mexregkan/claude-for-researchers/cross-validate
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 Mexregkan/claude-for-researchers --skill cross-validate
Clone the repo
git clone --depth 1 https://github.com/Mexregkan/claude-for-researchers

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 cross-validate

README.md
[![agentmods](https://agentmods.dev/badge/skills/mexregkan/claude-for-researchers/cross-validate/github.svg)](https://agentmods.dev/skills/mexregkan/claude-for-researchers/cross-validate)
Your own site
<a href="https://agentmods.dev/skills/mexregkan/claude-for-researchers/cross-validate"><img src="https://agentmods.dev/badge/skills/mexregkan/claude-for-researchers/cross-validate/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 cross-validate

Your own site · 80×15
<a href="https://agentmods.dev/skills/mexregkan/claude-for-researchers/cross-validate"><img src="https://agentmods.dev/badge/skills/mexregkan/claude-for-researchers/cross-validate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 834 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 pass 7 Sept 2026
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 $0.00036 $0.00834
Opus 5 $0.00018 $0.00417
Sonnet 5 $0.00007 $0.00167
Haiku 4.5 $0.00004 $0.00083

Measured 11d ago against content hash 9c1f0d26484c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

cross-validate 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 11d 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.

starter/.claude/skills/cross-validate/SKILL.md · 94 lines

How it starts

The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/cross-validate

Format a physics or mathematics claim for cross-model validation.

Use this when Claude has produced a result you want to check against a second AI model (Gemini, ChatGPT, or a fresh Claude context). Different models fail in different ways on the same physics, so agreement between models is meaningful evidence; disagreement tells you exactly where to look harder.

Inspired by the "hallucination orthogonality" principle and council-mode verification in flonat/claude-research, and the physics-specific failure modes documented by Tim Andersen (How to use Claude to do physics).

Usage

/cross-validate "the Gaussian integral sqrt(pi) follows from squaring and polar coordinates"
/cross-validate  (no argument — validate the last substantial result)

Steps

Step 1 — State the claim precisely. Write the claim as a self-contained statement including:

  • The exact formula or result
  • All notation and conventions needed to read it (do not assume the other model shares your conventions)
  • The domain of validity or the specific input values

Example:

Claim: The Gaussian integral I = ∫_{-∞}^{∞} e^{-x²} dx equals √π. Check this by computing I² = ∫∫ e^{-(x²+y²)} dx dy in polar coordinates, and confirm the radial integral gives π.

Step 2 — List the specific checkpoints. Identify what a second model should verify. Focus on the known Claude weak spots:

  • Dimensional analysis: are all quantities dimensionally consistent?
  • Sign conventions: which sign convention is being used and is it applied consistently?
  • Formula provenance: is this formula standard? Does it appear (with the same normalisation) in a named reference?
  • Special-case check: does the result reduce correctly at a known special value?
  • Step that looks too easy: any step summarised as "one computes" or "it follows that" — ask the other model to expand it.

Read the full file on GitHub · 94 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. 11d ago First seen · 94 lines · 36 tokens per session scan A 9c1f0d26484c

Subscribe to this mod's changes

cross-validate is a skill published in the GitHub repository Mexregkan/claude-for-researchers (52 stars, last pushed 8d ago), licensed MIT. It adds 36 tokens to every session and 834 once invoked, about $0.0002 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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