BC content-analytics
内容效果分析(v25.0合并content-closed-loop),计算播放/完播/互动/转化指标,生成S/A/B/C评级和优化建议+6步闭环(publish→recommend→feedback→analyze→optimize→learn)。触发词:内容分析/播放数据/完播率/互动统计/内容评级/闭环/CP-07 不触发:内容发布/内容模板/趋势发现
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
AnalyzerInfrastructureData and analyticstype and topics are labelled automatically from the skill text
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 10. 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 "tools" - note
frontmatter-keyunknown frontmatter key "dependencies"
Process rating: all ten parameters 51/100
- 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
- 30Running it twice. 2 mutating operations with no state check
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 45 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1183 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
- -43 reference files, but SKILL.md never points to them: the model will not open them
- +1No license
- +2Single-language instructions
- +3Description length 179: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 45 items
- +4Has examples (2 code blocks)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.
External checks
ClawHub: suspicious
The skill is mostly coherent with content analytics, but it also has broad database-write, cross-tenant sync, external tool, and persistent learning behavior that should be reviewed before installation.
LLM: suspicious (high) · 15 Aug 2026