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anneal

Use when the user wants to systematically fix AI code slop — duplicated logic, over-engineering, silent error swallowing, convention drift, cargo-cult patterns, and other LLM-introduced architectural decay — over a specified duration

72

Quality

88%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

77%

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

Highly actionable with a clear, validated workflow, but the single-file structure is over-long for a skill with no external references, and the anti-premature-exit messaging is repeated across several sections.

Suggestions

Consolidate the recurring "check the clock, dispatch, don't stop early" messaging into one section (e.g. Iron Law) and have later sections reference it rather than restating it, to tighten conciseness.

Consider moving the 10-item Slop Catalog and the subagent prompt template into a reference file (e.g. references/slop-catalog.md) referenced one level deep, since the orchestrator pastes them into subagent prompts anyway.

Drop or shrink the DOT graph — the numbered step-by-step list already conveys the same dispatch loop — to remove redundancy.

DimensionReasoningScore

Conciseness

The body is mostly specific and earns its tokens, but the "check the clock / dispatch" mantra repeats across Your Role, Iron Law, Preventing Premature Exit, Preventing Sabotaged Runs, and Red Flags, and the DOT graph largely duplicates the step-by-step list.

2 / 3

Actionability

Concrete commands (`date +%s`), exact progress-file paths and templates, a paste-ready subagent prompt, and a fixed commit message format (`anneal: <pattern> in <location>`) make the guidance copy-paste ready.

3 / 3

Workflow Clarity

The Safety Protocol is an explicit sequence with validation checkpoints — run tests for baseline, make one change, re-run tests, revert on new failures, commit only when passing — a clear validate→fix→revert feedback loop.

3 / 3

Progressive Disclosure

Sections are well-organized with a Quick Reference table, but the 280-line skill is monolithic; the slop catalog and subagent prompt template are inline content that could be split into one-level-deep reference files.

2 / 3

Total

10

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12

Passed

Description

100%

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 well-crafted description: concrete, third-person, with an explicit "Use when" trigger and a distinctive time-bounded framing that separates it from generic code-cleanup skills.

DimensionReasoningScore

Specificity

Enumerates concrete targets — "duplicated logic, over-engineering, silent error swallowing, convention drift, cargo-cult patterns" — naming the domain and the specific things fixed rather than vague abstractions.

3 / 3

Completeness

Explicitly answers both what ("systematically fix AI code slop") and when ("Use when the user wants to ... over a specified duration"), with an explicit trigger clause in third-person voice.

3 / 3

Trigger Term Quality

Includes natural phrases a developer would actually say — "AI code slop", "over-engineering", "duplicated logic" — alongside the explicit "Use when the user wants to" trigger construction.

3 / 3

Distinctiveness Conflict Risk

The time-bounded slop-fixing orchestrator niche ("over a specified duration") is distinct from general refactoring or review skills and unlikely to trigger for the wrong skill.

3 / 3

Total

12

/

12

Passed

Validation

100%

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

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
av/harbor
Reviewed

Table of Contents

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