BF fire-smoke-detection-analysis
Detects fire and smoke in video scenes. Supports both video stream and image analysis. Suitable for fire early warning scenarios such as security surveillance, forest fire prevention, and industrial parks. | 烟火检测技能，对视频场景中火情和烟雾进行检测，支持视频流和图片检测，适用于安防监控、森林防火、工业园区等火灾预警场景
As a process F 30/100 · 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.
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 (fire-smoke-detection-analysis) differs from the folder (smyx-fire-smoke-detection-analysis)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Execution cost. Instruction body is 1288 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
- -252 emoji in the instructions: noise for the model
- -32 of 4 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 266: enough signal without eating the budget
- +4Structure: 18 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 looks like a real cloud fire/smoke detection skill, but it silently creates and stores account identity/tokens and is configured to send media and credentials over plaintext development HTTP endpoints.
LLM: suspicious (high) · 7 Sept 2026