SKILLEMALL.ai

AC cd2flac

Convert CD audio archives (RAR files containing WAV+CUE pairs) into organized FLAC files. Handles RAR extraction, CUE-based track splitting, GBK encoding fix for Chinese filenames, multi-CD album organization, and auto-fetch synced lyrics from Netease Cloud Music (with Kugou fallback). Use whenever someone needs to extract and convert CD-quality audio archives (WAV+CUE in RAR/7z/ZIP) to per-track FLAC files. Also handles direct WAV+CUE pairs without archives.

ClawHub Agent Skills author: HANSHOJIN v1.3.1 MIT-0 5 files · 2 scripts body ≈ 841 tokens Open the sourceclawhub.ai↗ analyzed 15 d ago

Convert CD audio archives (RAR files containing WAV+CUE pairs) into organized FLAC files.

As a process C 60/100 · Has gaps — weak spots: result and completion, running it twice, progress reporting

GeneratorSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
Running it twice w 4
30
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 · 0

    ✓ No critical or high findings

    Files scanned: 5. 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 60/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 14 steps, 2 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 841 tokens

    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
    • +1No license
    • +2Single-language instructions
    • +3Description length 463: enough signal without eating the budget
    • +4Structure: 19 headings
    • +3Step-by-step instructions: 14 items
    • +4Has examples (10 code blocks)
    • +3All 2 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: suspicious
    This skill mostly does what it says, but it can delete source audio files unsafely and sends music metadata to external lyric services with weak disclosure and an insecure HTTP fallback.
    LLM: suspicious (high) · VirusTotal: · 16 Sept 2026