BC all-industry-officers
全行业职能群执行体系：任何行业、任何组织的职能任务开箱即用，由 15 个域级智能团队（总控官团队 + 人才官/财务官/行政官/数智官四大通用团队 + 情报官/认证官/内容官/活动官/客户官/运营官/分析官/流程官/合规官/知识官十大业务团队）的 375 种身份协作完成，双层全职能覆盖——行业天然通用层（人力资源、财务会计、行政办公、信息技术）+ 业务泛化通用层（情报采集、内容生产、活动运营、数据分析、知识管理、合规风控、客户运营、流程协同、资质认证、供应链运营十大业务流）。125个能力单元与任务一一对应，每个单元自带多重身份叠加（主领域身份+协同身份栈，全体系共 125 主身份+250 协同身份）与P实现（LLM/工具/人机/组合），每次执行任务时依次显示管线中所有能力单元完整信息卡并重点播报身份叠加，营造大量身份共同协作的多智能体感知；自带12条跨域编排管线、15个域级任务范本（每域一个，含该域全部任务具体执行时的执行输出范本——每个任务一个交付物本体样例）、行业/组织双校准机制与完整依赖拓扑知识图谱。触发词：任务团队、团队协作、行业通用、组织职能、人力资源、财务、行政办公、信息技术、技能体系、能力单元、身份叠加、P实现、多智能体协作、管线编排、行业校准、组织校准、招聘、绩效、薪酬、报销、预算、税务、会议、档案、印章、合同、差旅、接待、打印、印刷、名片、宣传册、IT支持、文件格式、格式转换、文档处理、OCR、业务、运营、情报、内容、活动、数据、知识、合规、客户、流程、认证、供应链、行业分析、竞品分析、市场调研、数据分析、培训、项目管理、资质认证、自媒体、新媒体、账号运营、内容发布、短视频、直播、AIO、all-industry-officers、meta-skill-system。
全行业职能群执行体系：任何行业、任何组织的职能任务开箱即用，由 15 个域级智能团队（总控官团队 + 人才官/财务官/行政官/数智官四大通用团队 + 情报官/认证官/内容官/活动官/客户官/运营官/分析官/流程官/合规官/知识官十大业务团队）的 375…
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
medium Broad scope
meta-broad-allowed-toolsSKILL.md:1Broad tool permissions pre-approved: Bashallowed-tools: Read Write Edit Glob Grep Bash
Files scanned: 19. 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") - note
frontmatter-keyunknown frontmatter key "display_name" - note
frontmatter-keyunknown frontmatter key "display_name_en" - note
frontmatter-keyunknown frontmatter key "description_zh" - note
frontmatter-keyunknown frontmatter key "description_en"
Process rating: all ten parameters 53/100
- 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
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 23 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2428 tokens
- 100Running it twice. No mutating operations
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
- +1No license
- +2Single-language instructions
- +3Description length 754: enough signal without eating the budget
- +4Structure: 24 headings
- +3Step-by-step instructions: 23 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (2 of 17)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.