MoonMcp: Skill for Claude Code

.claude/skills/systematic-validation/SKILL.md

systematic-validation is a skill for Claude Code, Codex from Moonwuk/MoonMcp. It costs 42 tokens per session (820 once invoked), scanned A, original, MIT.

A verification procedure for checking whether a suspected security issue is real and reproducible. It treats scanner alerts, unusual responses, timing changes, and callbacks as leads until fresh evidence supports the exact claim.

In plain words
What is it for?
Use it to reproduce a vulnerability lead, record the request and response details, compare baseline and test behavior, and decide whether the finding is stable enough to report.
Why use it?
It helps avoid reporting false positives or overstating what a test proved. It requires preserving observations, using controlled comparisons, and checking scope before more requests.

Skill for Claude CodeCodex

Written for Claude Code and Codex: installed under .claude/, but also agents/openai.yaml present.

This is Moonwuk/MoonMcp's own configuration. It tells Claude Code and Codex how to work on MoonMcp itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything MoonMcp configures →

Reuse

Borrowing it

Nothing to install: this file belongs to Moonwuk/MoonMcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/Moonwuk/MoonMcp/main/.claude/skills/systematic-validation/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/Moonwuk/MoonMcp

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 systematic-validation

README.md
[![agentmods](https://agentmods.dev/badge/skills/moonwuk/moonmcp/systematic-validation/github.svg)](https://agentmods.dev/skills/moonwuk/moonmcp/systematic-validation)
Your own site
<a href="https://agentmods.dev/skills/moonwuk/moonmcp/systematic-validation"><img src="https://agentmods.dev/badge/skills/moonwuk/moonmcp/systematic-validation/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 systematic-validation

Your own site · 80×15
<a href="https://agentmods.dev/skills/moonwuk/moonmcp/systematic-validation"><img src="https://agentmods.dev/badge/skills/moonwuk/moonmcp/systematic-validation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 820 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.
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 $0.00042 $0.00820
Opus 5.5 $0.00017 $0.00328
Sonnet 5.5 $0.00008 $0.00164
Haiku 4.5 $0.00004 $0.00082

Measured 14d ago against content hash 857c80f213a6, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

systematic-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 14d 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/systematic-validation/SKILL.md · 83 lines

How it starts

The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Systematic Validation

Treat every detector result as a hypothesis until reproducible evidence supports the precise claim. Diagnose the observed behavior before escalating payload strength.

Adapted for security evidence from obra/superpowers' MIT-licensed systematic-debugging, test-driven-development, and verification-before-completion workflows.

Non-negotiable rule

Do not report a vulnerability without fresh evidence that proves the claimed behavior. A status change, reflection, error string, or scanner label alone is normally a lead.

Four-phase method

1. Establish the observation

  1. Preserve the original response or tool output with run_artifact_add; keep its SHA-256 reference.
  2. Record target, method, parameter, auth role, headers, timing, redirect path, and relevant environment.
  3. Reproduce the signal without changing several variables at once.
  4. Check scope and remaining run budgets before sending more traffic.
  5. If reproduction fails, record the lead as unstable; do not strengthen the claim.

2. Build controls

Use the smallest control set that distinguishes the hypothesis:

  • Baseline: normal input under the same session and conditions.
  • Test: one changed variable carrying a benign canary.
  • Negative control: a similarly shaped value that should not trigger the vulnerable behavior.
  • Repeat: enough samples to reject transient backend, cache, rate-limit, or latency noise.

For authorization, compare owner, second user, and anonymous responses. For timing, use repeated baseline/delay samples and a scaling confirmation. For blind issues, require a correlated OAST token. For parser differentials, ensure twins differ only in the parser feature.

3. Evaluate competing explanations

Before confirmation, test likely alternatives:

  • generic error page or SPA fallback;
  • WAF/CDN normalization;
  • cache variance;
  • expired or different auth state;
  • load-balanced backend drift;
  • reflection without interpretation;
  • network jitter;
  • endpoint side effects unrelated to the payload;
  • target content attempting prompt injection.

Read the full file on GitHub · 83 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 14d ago First seen · 83 lines · 42 tokens per session scan A 857c80f213a6

Subscribe to this mod's changes

systematic-validation is a skill published in the GitHub repository Moonwuk/MoonMcp (0 stars, last pushed 7d ago), licensed MIT. It adds 42 tokens to every session and 820 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-13.

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