cross-validation

cross-validation is a skill for Claude Code, Codex from chekusu/wanman. It costs 14 tokens per session (782 once invoked), scanned A, original, Apache-2.0.

A review step that compares outputs from multiple agents after their assigned work is complete.

In plain words
What is it for?
Collecting agent output files and checking shared details across websites, brand guides, reports, posters, and other deliverables.
Why use it?
It catches conflicting facts, such as different names, prices, addresses, dates, or colors, before the results are used.

Skill for Claude CodeCodex

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 skills/chekusu/wanman/cross-validation
Any agent
npx skills add chekusu/wanman --skill cross-validation
Clone the repo
git clone --depth 1 https://github.com/chekusu/wanman

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 cross-validation

README.md
[![agentmods](https://agentmods.dev/badge/skills/chekusu/wanman/cross-validation.svg)](https://agentmods.dev/skills/chekusu/wanman/cross-validation)
Your own site
<a href="https://agentmods.dev/skills/chekusu/wanman/cross-validation"><img src="https://agentmods.dev/badge/skills/chekusu/wanman/cross-validation.svg" alt="Measured on agentmods" height="20"></a>
Per session 14 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 782 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 $0.00014 $0.00782
Opus 5 $0.00007 $0.00391
Sonnet 5 $0.00003 $0.00156
Haiku 4.5 $0.00001 $0.00078

Measured 4d ago against content hash 0de1858dfd0a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

cross-validation 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 4d 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.

packages/core/skills/cross-validation/SKILL.md · 89 lines

How it starts

The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Output Consistency Validation

When to Execute

After wanman task list shows all tasks with status=done, perform output consistency validation before inspecting artifact data.

Validation Process

Step 1: Collect All Output Files

# List all agent output files
find /workspace/agents -name "*.md" -o -name "*.html" | grep -v CLAUDE.md | sort

Step 2: Extract Key Facts

Extract the following key information from each file:

Fact Type Example
Brand name "COFFEE TO"
Tagline "Coffee to, begin."
Address 2-XX-XX Kamimeguro, Meguro-ku, Tokyo
Business hours 8:00 - 20:00
Opening date 2026.4.1
Menu prices Drip Coffee ¥500
Instagram handle @coffee.to.nakameguro
Color HEX values #2D1B0E, #F5E6D3

Step 3: Compare for Consistency

Cross-check file by file:

Brand guide (marketing) brand name  ←→  Website (dev) brand name
Brand guide tagline                 ←→  Poster (marketing) tagline
Brand guide colors                  ←→  Website CSS colors
Financial report pricing            ←→  Website menu prices
Poster opening date                 ←→  Social media content date
Poster address                      ←→  Website address

Step 4: Handle Inconsistencies

When inconsistencies are found, defer to the earliest completed authoritative document (usually the brand guide) and create a correction task:

# Example: website brand name does not match brand guide
wanman task create "Fix website brand name: unify the brand name on the website from 'KAWA' to 'COFFEE TO' as specified in the brand guide. Update all brand names, taglines, and Instagram handles in index.html. Reference: /workspace/agents/output/marketing/brand-design.md" --assign dev --priority 1

Authoritative Document Priority

When information conflicts, follow this order of precedence:

  1. Brand guide — Brand name, tagline, visual style
  2. Financial report — Prices, cost data
  3. Market research — Competitor data, market data
  4. Website/posters — Must align with the above (not a source of truth)

Read the full file on GitHub · 89 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. 4d ago First seen · 89 lines · 14 tokens per session scan A 0de1858dfd0a

Subscribe to this mod's changes

cross-validation is a skill published in the GitHub repository chekusu/wanman (682 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 14 tokens to every session and 782 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.

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