AC yotta-anti-shallow
元谨 —— 当检测到用户需要深入分析、全链路验证、根因追溯、严谨执行、细致检查时激活规则；此外，任何达到 L3（复杂）及以上复杂度的任务也会自动适用本规则，无需用户显式唤醒。触发：防敷衍、敷衍、灌水、糊弄、水货、深入、严谨、细致、仔细、全链路、根因、审视、反思、自我检查、追溯、验证、证明、认真、别糊弄、上规则、不要敷衍、恢复规则、加载防敷衍。边界：质量纪律规则，不执行代码、不调用外部工具，不替代测试或人工复核。
元谨 —— 当检测到用户需要深入分析、全链路验证、根因追溯、严谨执行、细致检查时激活规则；此外，任何达到…
As a process C 53/100 · Has gaps — 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.
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: 11. 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 "agent_created"
Process rating: all ten parameters 53/100
- 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
- 100Tools and files. No external tools needed
- 100Steps. 41 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1701 tokens
- 100Running it twice. No mutating operations
- 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
- +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 207: enough signal without eating the budget
- +4Structure: 23 headings
- +3Step-by-step instructions: 41 items
- +4Has examples (8 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.
External checks
ClawHub: suspicious
This is a disclosed quality-control skill, but it broadly and persistently changes agent behavior and includes installers that can write across many agent skill directories.
LLM: suspicious (high) · 8 Sept 2026