SKILLEMALL.ai
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AC ultimate-music-manager

Organises a messy local music library into a clean Language/Artist/Album hierarchy using acoustic fingerprinting, deduplication, metadata enrichment, and optional Spotify sync. Use when: (1) User wants to sort or clean up a folder of audio files, (2) User has untagged or badly-tagged MP3/FLAC/M4A files, (3) User wants to identify unknown songs via Shazam fingerprinting, (4) User wants to deduplicate audio files by content hash, (5) User wants to enrich metadata with iTunes artwork and LrcLib lyrics, (6) User wants to sync their local library to Spotify playlists.

ClawHub Agent Skills author: Rohit Burani v1.0.1 MIT-0 10 files · 4 scripts body ≈ 3 656 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 64/100 · Has gaps — weak spots: result and completion, when it triggers, progress reporting

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
98
Quality 40%
89
Run on models
none yet
Process rating
C
64/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Exfiltration read-dotenv scripts/preflight.sh:110
      Reads a .env file (quoted — discussed, not commanded)
      info "  cp .env.example .env"
      quoted
    • low Exfiltration read-dotenv scripts/preflight.sh:119
      Reads a .env file (code comment)
      # Source .env manually to read MUSIC_ROOT (config.py uses python-dotenv,
      comment

    Files scanned: 10. 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 64/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 20 steps
    • 100Failures and branches. 4 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3656 tokens
    • 100Running it twice. Mutating operations check current state
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 12 top-level sections: this looks like several domains in one skill
    • low The response is described with custom markup (12 tags): a typed call is more reliable

    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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • -2localhost URLs: will not work for another user
    • +1No license
    • +2Single-language instructions
    • +3Description length 569: enough signal without eating the budget
    • +4Structure: 27 headings
    • +3Step-by-step instructions: 20 items
    • +4Has examples (10 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +3All 3 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    External checks

    ClawHub: suspicious
    This music organizer is mostly aligned with its purpose, but it needs Review because it can broadly reorganize local music files, uses optional Spotify account access, and has some under-disclosed or unsafe execution details.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026