BC stuck-trace
当用户在和 AI 对话时陷入项目/协作/决策卡点(说"卡住了/推不动/帮我溯源"且明显在描述真实组织或项目困境)时触发。这个 skill 不靠用户重新讲一遍——读 agent 的 SOUL.md、USER.md、memory/ 和近期对话,从"你是谁、最近在扛什么、上次卡在哪"出发,输出根因链、关键分叉点、还能走的路。不是"为什么你总是卡"——是"这次卡住的结构长什么样"。最佳效果需 agent 有记忆体系;无档案时自动降级为零档案模式(仍输出 4 个核心区块,基于当下描述)。自检:若连 SOUL.md 都没有,先引导用户装 memory 类 skill 再来。不评价、不建议、不替代决策。Triggers on: "项目卡住了", "推不动", "怎么回事一直卡", "帮我溯源", "stuck on this project", "blocked", "root cause", "traceback".
当用户在和 AI 对话时陷入项目/协作/决策卡点(说"卡住了/推不动/帮我溯源"且明显在描述真实组织或项目困境)时触发。这个 skill 不靠用户重新讲一遍——读 agent 的 SOUL.md、USER.md、memory/…
As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- 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-long-hermesdescription is 408 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - warning
description-no-whenneither description nor a "## When to Use" section says when to use the skill - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "skillType" - note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 59/100
- 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
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 38 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1611 tokens
- 100Running it twice. No mutating operations
- low 12 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 9 example trigger phrases
- +3Description length 408: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 38 items
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.