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CC scientific-inquiry-en

Rigorous evidence-based inquiry: decompose fuzzy questions, retrieve & grade evidence (S/A/B/C/D), cross-validate, and output conclusions with confidence intervals. Includes Step 0 user confirmation to prevent direction drift.

ClawHub Agent Skills author: HIT_LWY v1.0.1 MIT-0 2 files body ≈ 3 482 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

Rigorous evidence-based inquiry: decompose fuzzy questions, retrieve & grade evidence (S/A/B/C/D), cross-validate, and output conclusions with confidence…

As a process C 51/100 · Has gaps — References files that are not bundled: URL

ProcedureYouTubeInfrastructureData and analyticsMarketingtype 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
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
64
Run on models
none yet
Process rating
C
51/100
Has gaps
References files that are not bundled: URL
Tools and files w 18
0
Result and completion w 14
0
Consistency w 8
40
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.
  2. The text references files that are not there: add them or drop the references.
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 · 0

✓ No critical or high findings

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")
  • warning missing-ref reference to a missing file: URL

Process rating: all ten parameters 51/100

Will not run. References files that are not bundled: URL
  • 0Tools and files. 1 referenced file(s) missing: URL
  • 0Result and completion. Does not say what the result is
  • 40Consistency. Frontmatter name (scientific-inquiry-en) differs from the folder (scientific-inquiry)
  • 50Failures and branches. 0 branches, has a failure section
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 70 steps
  • 100Execution cost. Instruction body is 3482 tokens
  • 100Running it twice. Mutating operations check current state
  • 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
  • -220 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 226: enough signal without eating the budget
  • +4Structure: 21 headings
  • +3Step-by-step instructions: 70 items
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: suspicious
This is mostly a research workflow skill, but it also asks the agent to persist feedback and modify the skill itself, which needs review before installation.
LLM: suspicious (high) · VirusTotal: · 16 Sept 2026