BF inspection-record-digester
将现场拍摄或扫描的检查记录表格（质量巡检、设备点检、体系审核）进行视觉识别、结构化、合并清洗与分析，产出 Markdown 分析报告与 CSV 结构化数据。
将现场拍摄或扫描的检查记录表格（质量巡检、设备点检、体系审核）进行视觉识别、结构化、合并清洗与分析，产出 Markdown 分析报告与 CSV 结构化数据。
As a process F 31/100 · Will not run — References files that are not bundled: references/table-schemas.md, references/recognition-review.md, references/analysis-dimensions.md
ProcedureData and analyticsAI and agentstype 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: 2. 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/table-schemas.md - warning
missing-refreference to a missing file: references/recognition-review.md - warning
missing-refreference to a missing file: references/analysis-dimensions.md - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName"
Process rating: all ten parameters 31/100
Will not run. References files that are not bundled: references/table-schemas.md, references/recognition-review.md, references/analysis-dimensions.md
- 0Tools and files. 3 referenced file(s) missing: references/table-schemas.md, references/recognition-review.md, references/analysis-dimensions.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
- 40Consistency. Frontmatter name (inspection-record-digester) differs from the folder (skill-inspection-record-digester)
- 100Steps. 36 steps
- 100Execution cost. Instruction body is 816 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)
- +3Description length 78: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +4Structure: 12 headings
- +3Step-by-step instructions: 36 items
- +4Has examples (1 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 56.
External checks
ClawHub: clean
This skill appears to be a disclosed table-recognition workflow for user-provided inspection images, with no hidden persistence, credential access, or exfiltration behavior found.
LLM: benign (high) · VirusTotal: · 17 Jul 2026