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Red-team protocol for validating numerical claims before promoting them from tentative to real. 5 gates: literature baseline, observable audit, claim taxonomy,

ClawHub Agent Skills author: Deepak Vaid v1.0.0 MIT-0 2 files body ≈ 1 301 tokens Open the sourceclawhub.ai↗ analyzed 16 d ago

Red-team protocol for validating numerical claims before promoting them from tentative to real.

As a process C 58/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerData and analyticstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
C
88/100
safety, quality, tests
Safety 60%
98
Quality 40%
72
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 2

✓ No critical or high findings

Medium and low: 2
  • low Risky intent intent-offensive-security skill-card.md:2
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    Red Team is a protocol for validating numerical claims through five written gates before treating tentative observations as reportable results. <br>
  • low Risky intent intent-offensive-security SKILL.md:10
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    Before promoting *any* numerical claim from "tentative observation" to "finding worth reporting, committing, or dashboarding," run this protocol. No exceptions. The red team is a skeptical colleague w

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 58/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 2 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 100Tools and files. No external tools needed
  • 100Steps. 32 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1301 tokens
  • 100Progress reporting. Reports progress

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 159: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 32 items
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: clean
This skill is a benign review checklist for validating numerical claims and does not request privileged access, hidden execution, or unrelated data handling.
LLM: benign (high) · VirusTotal: · 24 Jul 2026