BC ai-self-evolution
记录经验、错误与修正，持续改进。触发场景：命令失败 | 操作出错 | 用户纠正（不对、实际上、你错了） | 功能请求（能不能、我希望、有没有办法） | API或工具失败 | 知识过时 | 发现更优做法 | 重复模式 | 非显而易见的问题。执行重大任务前先回顾历史经验。会话开始时回顾，会话结束时总结。
As a process C 58/100 · 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: 19. 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")
Process rating: all ten parameters 58/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 100Tools and files. No external tools needed
- 100Steps. 50 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1452 tokens
- 100Running it twice. No mutating operations
- 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
- -33 of 3 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 150: enough signal without eating the budget
- +4Structure: 22 headings
- +3Step-by-step instructions: 50 items
- +4Has examples (6 code blocks)
- +4Reference files are cited in the instructions (1 of 5)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.
External checks
ClawHub: suspicious
This is a disclosed agent memory/logging skill, but it can automatically save conversation and error details into persistent project and agent-memory files without strong consent or redaction controls.
LLM: suspicious (high) · VirusTotal: · 29 May 2026