BF agent-fact-check-verify
嚴謹多來源資訊查核與可信度判定技能。用於「查證/核實/核實這個/是真的嗎/是否正確」類請求，整合政府、官方、主流媒體、事實查核站、X(Twitter)、Reddit 等來源，採用內部 100 分制規則化評分（不對使用者公開分數），並強制 Tavily 優先與明確 fallback 規則。
As a process F 40/100 · Will not run — References files that are not bundled: references/scoring-rubric.md, references/source-policy.md
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: references/scoring-rubric.md - warning
missing-refreference to a missing file: references/source-policy.md
Process rating: all ten parameters 40/100
Will not run. References files that are not bundled: references/scoring-rubric.md, references/source-policy.md
- 0Tools and files. 2 referenced file(s) missing: references/scoring-rubric.md, references/source-policy.md
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 100Steps. 69 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 662 tokens
- 100Running it twice. No mutating operations
- low 10 top-level sections: this looks like several domains in one skill
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
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 144: enough signal without eating the budget
- +4Structure: 17 headings
- +3Step-by-step instructions: 69 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.
External checks
ClawHub: clean
This is a fact-checking skill that uses disclosed external search sources and does not install code, persist, or request unusual privileges.
LLM: benign (high) · VirusTotal: · 17 Jul 2026