CC meta-optimize
Analyze ARIS usage logs and propose optimizations to SKILL.md files, reviewer prompts, and workflow defaults. Outer-loop harness optimization inspired by Meta-Harness (Lee et al., 2026). Use when user says "优化技能", "meta optimize", "improve skills", "分析使用记录", or wants to optimize ARIS's own harness components based on accumulated experience.
Analyze ARIS usage logs and propose optimizations to SKILL.md files, reviewer prompts, and workflow defaults. Outer-loop harness optimization inspired by…
As a process C 65/100 · Has gaps — References files that are not bundled: ../shared-references/reviewer-backends.md, ../shared-references/capture-antipatterns.md, ../shared-references/output-versioning.md
The same skill appears in 1 more place: Auto-claude-code-research-in-sleep
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
How to improve
- The text references files that are not there: add them or drop the references.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
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medium Broad scope
meta-broad-allowed-toolsSKILL.md:1Broad tool permissions pre-approved: Bash(*)allowed-tools: Bash(*) Read Write Edit Grep Glob mcp__antigravity__antigravity mcp__antigravity__antigravity-reply mcp__grok__grok mcp__grok__grok-reply mcp__claude-review__review mcp__claude-review__
Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: ../shared-references/reviewer-backends.md - warning
missing-refreference to a missing file: ../shared-references/capture-antipatterns.md - warning
missing-refreference to a missing file: ../shared-references/output-versioning.md - warning
missing-refreference to a missing file: ../shared-references/output-manifest.md - warning
missing-refreference to a missing file: ../shared-references/output-language.md
Process rating: all ten parameters 65/100
- 0Tools and files. 5 referenced file(s) missing: ../shared-references/reviewer-backends.md, ../shared-references/capture-antipatterns.md, ../shared-references/output-versioning.md
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 7 mutating operations with no state check
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 4382 tokens
- 100Steps. 35 steps
- 100Result and completion. Output format and completion criterion are stated
- 100Failures and branches. 3 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 10 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)
- +1No license
- +2Single-language instructions
- +5Description quotes 3 example trigger phrases
- +3Description length 342: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 35 items
- +3Output format is stated explicitly
- +4Has examples (8 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.