BF emotion-analysis
Professional discernment of subtle cues! It performs detailed analysis and recognition of facial micro-expressions, outputs precise emotional state reports, and unveils true inner emotional activities. | 微观情绪（微表情）识别分析工具，专业察言观色！针对人物面部微表情进行细致分析识别，输出精准的情绪状态分析报告，揭示真实内心情绪活动
As a process F 30/100 · Will not run — weak spots: steps, result and completion, when it triggers
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: 30. 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")
Process rating: all ten parameters 30/100
- 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
- 25Steps. 1 steps
- 40Consistency. Frontmatter name (emotion-analysis) differs from the folder (smyx-emotion-analysis)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Execution cost. Instruction body is 1633 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)
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- -257 emoji in the instructions: noise for the model
- -32 of 4 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 269: enough signal without eating the budget
- +4Structure: 19 headings
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.
External checks
ClawHub: suspicious
This skill performs the advertised cloud emotion-analysis workflow, but it also silently binds use to local identity records and remote account/token flows for sensitive face media.
LLM: suspicious (high) · 27 Aug 2026