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aris-meta-apply

Human-invoked landing of selected ARIS meta-optimization patches after a fresh cross-family jury, with backups and provenance receipts.

Quality

69%

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./skills/aris-meta-apply/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

73%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.

The body is a strong operational document: a clearly sequenced, validation-heavy workflow with rollback, concrete CLI commands, and precise refusal criteria for a privileged mutation gate. Its weaknesses are token efficiency — rules are stated twice and design rationale is inlined — and a few executable details that are delegated to external shared-reference documents rather than shown inline.

Suggestions

Consolidate 'The non-negotiable rules' and 'Key Rules' into a single authoritative list (the latter currently restates the former nearly verbatim), keeping only cross-references.

Trim design-history narrative ('The earlier design trusted a jury_verdict: pass field...') to one line of rationale; the full history belongs in a project doc, not the skill body.

Inline a one-line example of the codex jury MCP call (JSON payload with model/config/sandbox/cwd) so Step 1 is copy-paste executable without reading reviewer-routing.md.

DimensionReasoningScore

Conciseness

The body is dense and operational (exact CLI flags, jury parameters, log schemas) but includes unnecessary material: the three non-negotiable rules are restated nearly verbatim in 'Key Rules', and sections like 'The acquittal is generated HERE, not relayed' and 'Provenance is a receipt, not an acquittal of correctness' carry design-history rationale that could be tightened. This matches anchor 3 (mostly efficient, some unnecessary explanation) rather than 4, where over-explanation would be only minor.

3 / 5

Actionability

Guidance is largely executable: concrete commands (`python3 "$PROVENANCE" check --author ... --reviewer ...`, `stamp ... --trace-mode full`), exact jury call parameters (`model: gpt-6-astra`, `config: {"model_reasoning_effort": "ultra"}`, `sandbox: read-only`), and exact JSONL log shapes. It falls short of anchor 5 because the $PROVENANCE resolution chain and the codex MCP call payload are delegated to external documents/prose rather than shown as a copy-paste-ready example.

4 / 5

Workflow Clarity

The Step 0→3 sequence is explicit with validation checkpoints throughout: refuse-default ('any failure ⇒ skip & report, never silently apply'), verify-before-mutation ('Missing or mismatched artifacts mean skip, even if the helper exited successfully'), a backup-before-edit rule, and a restore-on-failure feedback loop ('If apply, stamp, or logging fails, restore the target ... Do not claim LANDED for a partial transaction'). This matches anchor 5 (explicit validation, error-recovery loops) — the strongest dimension of the skill.

5 / 5

Progressive Disclosure

The single-file body is well-sectioned and every external link (reviewer-independence.md, review-scope-limits.md, integration-contract.md §2, reviewer-routing.md, review-tracing.md, skill-governance.md) is one level deep and signaled with its purpose ('capability fallback is limited to explicit pre-thread model/effort errors'). It is 4 rather than 5 because no bundle files ship with the skill, key operational detail (helper resolution) lives entirely in an external contract, and the inlined duplicated rules could be consolidated or moved out.

4 / 5

Total

16

/

20

Passed

Description

53%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.

The description communicates a clear, distinctive niche and an unambiguous 'what', but it is written in project-internal vocabulary ('cross-family jury', 'provenance receipts') and omits any explicit 'when to use' trigger clause. A user or model scanning descriptions would recognize the domain but not naturally surface this skill from everyday phrasing.

Suggestions

Add an explicit trigger clause, e.g. 'Use when the user asks to apply, land, or commit staged ARIS meta-optimization patches' — this would lift completeness and trigger-term quality together.

Replace or gloss insider jargon with natural user phrasing: 'independent cross-model review' instead of 'fresh cross-family jury', and 'audit trail of who reviewed and approved' instead of 'provenance receipts'.

Enumerate the concrete actions performed (run an independent review of each staged diff, back up targets, apply the patch, record who authored and who approved it) so capability coverage is comprehensive rather than implied.

DimensionReasoningScore

Specificity

The description names the domain ("ARIS meta-optimization patches") and a few concrete elements ("landing", "backups", "provenance receipts"), but the actions are few and framed in internal jargon, leaving coverage of what the skill actually does (jury review, refuse-on-KILL, cross-family check) incomplete. It matches anchor 3 (domain plus 1-2 concrete actions, not comprehensive) rather than 4, which requires several specific actions with only minor gaps.

3 / 5

Completeness

The 'what' is clear (lands selected staged patches with backups and receipts), but the 'when' is only weakly implied by "Human-invoked" — there is no explicit 'Use when...' clause or equivalent trigger guidance, which caps this dimension at 3 per the judging guidelines. Not 4 because the invocation condition is never explicitly stated.

3 / 5

Trigger Term Quality

"patches", "landing", and "backups" are terms a user might naturally say, but "fresh cross-family jury" and "provenance receipts" are insider jargon, and there are no common synonyms or explicit trigger phrases. This lands at anchor 3 (some relevant keywords, missing common variations) rather than 4 (good keyword coverage with only a few natural terms missing).

3 / 5

Distinctiveness Conflict Risk

"Human-invoked landing of selected ARIS meta-optimization patches" carves out a clear niche (the apply/landing gate) with minimal conflict risk against unrelated skills. It is 4 rather than 5 because it shares 'meta-optimization' vocabulary with the closely related producer skill (/aris-meta-optimize) and states no distinct trigger phrases to separate the two.

4 / 5

Total

13

/

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: 7 suspicious

Warning

Total

13

/

16

Passed

Repository

OpenLAIR/dr-claw

Path

skills/aris-meta-apply/SKILL.md

Reviewed

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