BF true-seeing
审核 AI 生成文章中的可验证事实，通过 web search 逐条校验，输出差异报告并支持用户审批替换。当用户需要事实核查、验证文章准确性、检查数据日期金额是否正确、去除 AI 幻觉内容、或 fact-check 一篇文章时使用。触发于"事实核查"、"验一下这些数据"、"检查事实"、"去幻觉"、"fact check"、"核实文章"、"核实这段话"、"帮我对一下数据"、"这篇文章里的数字对不对"。不适用于语法纠错、翻译校对、纯观点验证、文风调整。
As a process F 35/100 · Will not run — References files that are not bundled: {source_url}, references/fact-extraction-rules.md, references/search-query-templates.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.
- 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: 7. 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: {source_url} - warning
missing-refreference to a missing file: references/fact-extraction-rules.md - warning
missing-refreference to a missing file: references/search-query-templates.md - warning
missing-refreference to a missing file: references/verification-criteria.md
Process rating: all ten parameters 35/100
- 0Tools and files. 4 referenced file(s) missing: {source_url}, references/fact-extraction-rules.md, references/search-query-templates.md
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 100Steps. 85 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1923 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
- +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
- +5Description quotes 4 example trigger phrases
- +3Description length 226: enough signal without eating the budget
- +4Structure: 25 headings
- +3Step-by-step instructions: 85 items
- +4Has examples (6 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.