AD verification-gate
代码改完后的验证门禁。完成 feature / 重大变更 / 创建 PR / 重构 / 声称「修完」前使用——跑 8 阶段验证，其中 e2e 功能 + 真机是 READY 硬门禁（编译过 ≠ 功能可用）。覆盖 Tauri 桌面 / Web / 服务 / Skill 四类分支。本地即可跑完整验证，CI 是可选自动化强化（平台不限 GitHub Actions）。不要用于：业务领域验证、Skill 质量审查（用 skill-lint）、纯文档变更、一次性脚本。
代码改完后的验证门禁。完成 feature / 重大变更 / 创建 PR / 重构 / 声称「修完」前使用——跑 8 阶段验证，其中 e2e 功能 + 真机是 READY 硬门禁（编译过 ≠ 功能可用）。覆盖 Tauri 桌面 / Web / 服务 / Skill 四类分支。本地即可跑完整验证，CI…
As a process D 45/100 · 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: 9. 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 "homepage"
Process rating: all ten parameters 45/100
- 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
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 4 mutating operations with no state check
- 60Tools and files. Uses tools (node) that frontmatter does not declare
- 100Steps. 40 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2141 tokens
- 100Progress reporting. Reports progress
- 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 230: enough signal without eating the budget
- +4Structure: 26 headings
- +3Step-by-step instructions: 40 items
- +4Has examples (9 code blocks)
- +4Reference files are cited in the instructions (5 of 5)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.