AC token-slim
Guided token optimization for AI agent workspaces. Triggers on phrases like "save tokens", "optimize tokens", "context window too large", "memory files too big", "scan my workspace", "trim workspace", "find token waste", "再扫一下", "帮我省 Token", "优化 Token 使用", "上下文太长了", "内存文件太大", "还有哪里可以优化". Also handles brutal-mode toggle: "enable brutal mode", "disable brutal mode", "开启狂暴模式", "关闭狂暴模式". On first use walks the user step-by-step through workspace cleanup; supports on-demand re-scans at any time. Works on OpenClaw, Claude Code, and any agent runtime with a writable working directory.
Guided token optimization for AI agent workspaces.
As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- 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: 8. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 54/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 1 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 85Steps. 23 steps, 2 vague phrases
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1748 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
- +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 16 example trigger phrases
- +3Description length 584: enough signal without eating the budget
- +4Structure: 17 headings
- +3Step-by-step instructions: 23 items
- +4Has examples (9 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 96.