BF intelligence-brain
AI原生公司情报大脑引擎：八步代谢管线（采集→解析→拆解→整理→合并→使用→删除→举一反三）+跨文件推论（三条日报拼出一个真相）+三通道神经链冗余+四级信息密级自动路由。信息吃进去，决策吐出来——大脑不是数据库，是消化系统。触发词：「公司大脑」「情报引擎」「信息代谢」「知识图谱」「决策支持」「AI大脑」「情报处理」「信号处理」
AI原生公司情报大脑引擎：八步代谢管线（采集→解析→拆解→整理→合并→使用→删除→举一反三）+跨文件推论（三条日报拼出一个真相）+三通道神经链冗余+四级信息密级自动路由。信息吃进去，决策吐出来——大脑不是数据库，是消化系统。触发词：「公司大脑」「情报引擎」「信息代谢」「知识图谱」「决策支持」「AI大脑」「情报处理」「…
As a process F 33/100 · Will not run — References files that are not bundled: references/pipeline-playbook.md, references/inference-patterns.md, references/neural-chain-design.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: 0. 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/pipeline-playbook.md - warning
missing-refreference to a missing file: references/inference-patterns.md - warning
missing-refreference to a missing file: references/neural-chain-design.md - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "summary"
Process rating: all ten parameters 33/100
- 0Tools and files. 3 referenced file(s) missing: references/pipeline-playbook.md, references/inference-patterns.md, references/neural-chain-design.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
- 30Running it twice. 1 mutating operations with no state check
- 100Steps. 36 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 894 tokens
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
- +2Single-language instructions
- +3Description length 164: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 36 items
- +4Has examples (4 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 58.