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aris-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.

Quality

84%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

81%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A highly actionable, well-sequenced workflow skill with strong validation gates and evidence discipline throughout. Its weaknesses are repetition of the same governance invariants multiple times and a monolithic body that inlines reference-grade material (prompt template, event schema) that a bundle file would carry better.

Suggestions

State the advisory-vs-binding-verdict boundary once in a single 'Landing gate' section and reference it from Steps 4 and 6 instead of repeating the full disclaimer verbatim.

Consolidate the model-delta deletion rules (Step 1 model-delta analysis, Step 2 example row, Key Rules) into one authoritative passage with the others pointing to it.

Move the Step-4 codex prompt template and the Event Schema Reference into reference files to shorten SKILL.md and improve progressive disclosure.

DimensionReasoningScore

Conciseness

The body is dense and non-obvious with no basic-concept padding, but key governance points repeat noticeably: the 'advisory only, not the landing verdict' disclaimer appears ~4 times (Step 4 header, Step 4 note, Step 6, Key Rules) and the model-delta deletion-evidence rule ~3 times. This matches anchor 3 ('mostly efficient but could be tightened') rather than 4 given the volume of verbatim repetition.

3 / 5

Actionability

The skill provides copy-paste-ready bash for the availability gate and the json.dumps ledger append, a complete adversarial-review prompt template, a concrete diff example, a manifest row schema, an event-schema reference, and exact marker-file formats. Everything needed to execute is written out, matching anchor 5.

5 / 5

Workflow Clarity

Steps 0–6 are clearly sequenced with explicit validation checkpoints and feedback loops: exit on <5 invocations, REVIEW_UNAVAILABLE on missing reviewers, reviewer score <7 triggering an evidence-needs explanation, a 'Changes NOT Made (insufficient evidence)' report section, and a human-gated staging step. This matches the anchor-5 pattern of validate → fix → re-check.

5 / 5

Progressive Disclosure

Cross-file references are one level deep and clearly signaled with links plus purpose (integration-contract §2, reviewer-routing.md, acceptance-gate.md, output protocols). It is not 5 because with no bundle of its own, ~440 lines of content that could live in reference files — notably the full Step-4 codex prompt template and the Event Schema Reference — are inlined in SKILL.md.

4 / 5

Total

17

/

20

Passed

Description

83%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description with an explicit what-and-when structure, third-person voice, and natural bilingual trigger phrases. Its main gaps are incomplete coverage of what the skill actually does (bottleneck analysis, staging patches) and some missing trigger synonyms, plus slight overlap risk with the sibling applier skill.

Suggestions

Mention that the skill ranks optimization opportunities, names the current pipeline bottleneck, and stages patch proposals, so the 'what' covers its actual outputs.

Add one or two common English trigger variations such as 'tune skills' or 'harness maintenance' to broaden natural keyword coverage.

Disambiguate from the sibling applier in the description itself (e.g. 'proposes only; landing changes is /aris-meta-apply') to reduce wrong-skill triggering.

DimensionReasoningScore

Specificity

"Analyze ARIS usage logs and propose optimizations to SKILL.md files, reviewer prompts, and workflow defaults" names two concrete actions aimed at multiple specific targets. It matches anchor 4 (several specific actions, minor gaps) rather than 5 because core activities like bottleneck ledgering, trigger-rate analysis, and patch staging are not mentioned.

4 / 5

Completeness

The description explicitly answers both what ("Analyze ARIS usage logs and propose optimizations to SKILL.md files, reviewer prompts, and workflow defaults") and when ("Use when user says...") with concrete trigger phrases, matching the anchor-5 example structure. It is not a 4 because the when-clause is fully explicit rather than merely present.

5 / 5

Trigger Term Quality

"Use when user says '优化技能', 'meta optimize', 'improve skills', '分析使用记录'" provides good natural-phrase coverage in both English and Chinese. It falls short of anchor 5 because common variations like 'tune skills', 'harness maintenance', or file/format-adjacent synonyms are missing.

4 / 5

Distinctiveness Conflict Risk

The ARIS-specific meta-optimization niche ("optimize ARIS's own harness components") is mostly distinct with minimal conflict against unrelated skills. It is not 5 because the propose-vs-apply boundary with the sibling /aris-meta-apply skill is only implied by 'propose', leaving minor overlap risk for users asking to 'optimize/fix skills'.

4 / 5

Total

17

/

20

Passed

Validation

81%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

relative_links

Relative link issues: 14 suspicious

Warning

Total

13

/

16

Passed

Repository

OpenLAIR/dr-claw

Path

skills/aris-meta-optimize/SKILL.md

Reviewed

Table of Contents

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