BF luban
鲁班（Luban）——Skill打磨工坊。把一个"能用的Skill"打磨成"能被理解、能被安装、能被传播、能被验证、能持续进化"的公共Skill资产。 方法论是工匠式的五个动作：验料（先挑战这个Skill的前提是否成立，不值得雕的料直说）、访行（联网寻找同类Skill，看清自己在生态里站什么位置）、过尺（结构、实测、活体三把尺一起量——活体指拉真实运行产物对账，绿色的CI会撒谎）、慢刨（冻结原版做基线，改动必须通过验证门才保留，否则回刀；验证手段尽量沉淀为仓库里的工具和规矩）、回炉（发布不是终点，留对标观察清单，下一轮从真实反馈进）。 当用户想要升级、优化、打磨、产品化、发布自己开发的Skill时使用。最终产出一份结构化的《Skill打磨报告》、可直接替换的改写片段，以及一张可截图传播的"出师证书"结果卡。 触发词包括但不限于：让鲁班看看这个skill、班门打磨、打磨我的skill、升级我的skill、优化这个skill、skill体检、skill审计、产品化我的skill、这个skill怎么发布、对标一下同类skill、为什么我的skill没人装、帮我把skill发到GitHub/ClawHub、改进SKILL.md。 即使用户只是丢来一个Skill目录、GitHub仓库链接或一段SKILL.md说"帮我看看怎么改"，只要上下文是想让Skill变得更好用、更可传播，都应该触发。 不要用于从零创建一个新Skill（用skill-creator）、不要用于普通的代码review（用code-review）、不要用于改写一段和Skill资产无关的普通提示语。
鲁班（Luban）——Skill打磨工坊。把一个"能用的Skill"打磨成"能被理解、能被安装、能被传播、能被验证、能持续进化"的公共Skill资产。…
As a process F 33/100 · Will not run — References files that are not bundled: scripts/backtest_*.py
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.
- 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: 3. 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: scripts/backtest_*.py
Process rating: all ten parameters 33/100
- 0Tools and files. 1 referenced file(s) missing: scripts/backtest_*.py
- 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
- 30Running it twice. 4 mutating operations with no state check
- 100Steps. 111 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2848 tokens
- low 14 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 3 example trigger phrases
- +3Description length 688: enough signal without eating the budget
- +4Structure: 35 headings
- +3Step-by-step instructions: 111 items
- +4Has examples (11 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.