BF 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.
As a process F 56/100 · Will not run — References files that are not bundled: URL
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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-whendescription does not say WHEN to use the skill (no "use when") - warning
missing-refreference to a missing file: URL
Process rating: all ten parameters 56/100
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)
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 70 steps
- 100Failures and branches. 4 branches, has a failure section
- 100Execution cost. Instruction body is 3482 tokens
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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: clean
This is a disclosed research-workflow skill; it has some sensitive persistence and network-use features, but they are visible, purpose-aligned, and gated enough for normal use.
LLM: benign (high) · VirusTotal: · 29 May 2026