BF smyx-public-place-group-emotion-index-analysis
Using fixed cameras in malls, exhibition halls, scenic areas and other public places, the system analyzes facial expressions of multiple people in the scene in real time (with anonymized expression recognition only), aggregates the distribution of emotions (happy, calm, irritated, surprised, sad, fearful, etc.), and computes an overall group-emotion index (0-100; higher = more positive). | 通过商场、展览馆、景区等公共场所的固定摄像头，实时分析场景中多人的面部表情（使用匿名化表情识别），统计各类情绪（愉悦、平静、烦躁、惊讶、悲伤等）的分布比例，计算整体情绪指数（0-100，数值越高代表群体情绪越积极）。该技能可帮助运营方了解顾客满意度、优化服务布局，或用于公共安全预警（如烦躁情绪比例过高可能预示冲突风险）。
Using fixed cameras in malls, exhibition halls, scenic areas and other public places, the system analyzes facial expressions of multiple people in the scene…
As a process F 34/100 · Will not run — weak spots: steps, result and completion, when it triggers
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 · 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 34/100
- 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
- 21Steps. 1 steps, 1 vague phrases
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1815 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
- -259 emoji in the instructions: noise for the model
- -32 of 4 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 554: 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.