BF simulated-peak-plot
生成模拟峰图（高斯峰），用于色谱、光谱或任何信号可视化。支持簇峰(N子峰各独立标注)/融峰(合成单标注)/单峰、负峰(倒峰)、标注控制(annotate)、扫描速率(scan_rate)、碰撞避让标注、自定义坐标轴/单位、CSV导出及CSV导入，**负峰（倒峰）**。
As a process F 35/100 · Will not run — References files that are not bundled: references/*.md
ProcedureData and analyticsInfrastructuretype 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.
- The text references files that are not there: add them or drop the references.
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: 12. 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") - warning
missing-refreference to a missing file: references/*.md - note
frontmatter-keyunknown frontmatter key "data_dir" - note
frontmatter-keyunknown frontmatter key "external_data_dir" - note
frontmatter-keyunknown frontmatter key "sensitive_access" - note
frontmatter-keyunknown frontmatter key "critical_write" - note
frontmatter-keyunknown frontmatter key "permission_weight" - note
frontmatter-keyunknown frontmatter key "create_permissions_md" - note
frontmatter-keyunknown frontmatter key "trigger" - note
frontmatter-keyunknown frontmatter key "trigger_negative" - note
frontmatter-keyunknown frontmatter key "meta_field_sync" - note
frontmatter-keyunknown frontmatter key "faq_unparsable" - note
frontmatter-keyunknown frontmatter key "faq_quality"
Process rating: all ten parameters 35/100
Will not run. References files that are not bundled: references/*.md
- 0Tools and files. 1 referenced file(s) missing: references/*.md
- 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
- 100Steps. 41 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1171 tokens
- 100Running it twice. No mutating operations
- low 11 top-level sections: this looks like several domains in one skill
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
- +2Single-language instructions
- +3Description length 134: enough signal without eating the budget
- +4Structure: 21 headings
- +3Step-by-step instructions: 41 items
- +4Has examples (9 code blocks)
- +4Reference files are cited in the instructions (8 of 8)
- +3All 1 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.
External checks
ClawHub: suspicious
The skill mostly matches a peak-plot generator, but its script secretly alters generated data and PNG pixels in ways users are not told about.
LLM: suspicious (high) · VirusTotal: · 25 Jun 2026