BD rebar-table-audit
从结构图纸（DWG/DXF）里找出设计方自带的“钢筋/材料工程数量表”（LINE 网格 + TEXT/MTEXT），还原成结构化表格，做 R001–R006 确定性算术核对（单根长×根数=总长、总长×单位理论重量=重量、行重量之和=表内声明合计等），输出 evidence.json、钢筋数量表.xlsx、report.md，每个单元格值和每条疑点都带图元 handle。适用于隧道/地下结构等算量审图场景，用户要“钢筋量”“导出钢筋表”“核对数量表”“钢筋表有没有算错”时使用。不适用：不做配筋图几何独立算钢筋（翻样），不处理扫描件/PDF/BIM 模型，不对算术不一致下“设计错误”结论。
从结构图纸（DWG/DXF）里找出设计方自带的“钢筋/材料工程数量表”（LINE 网格 + TEXT/MTEXT），还原成结构化表格，做 R001–R006 确定性算术核对（单根长×根数=总长、总长×单位理论重量=重量、行重量之和=表内声明合计等），输出…
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
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: 17. 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") - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "summary" - note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 46/100
- 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
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 14 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 812 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
- +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
- +5Description quotes 2 example trigger phrases
- +3Description length 296: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 14 items
- +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: 79.