SKILLEMALL.ai

AF galdr

OpenClaw skill for using galdr's ARC workflow to turn YouTube URLs or local audio files into grounded, time-ordered listening-experience prompts backed by listener-state traces: pattern, attention, pulse, heard pressure, surface balance/evidence, harmony, melody, overtones, and silence/re-entry structure. Use when asked to analyze a song, explain what makes a track work structurally, generate a listening experience, or extract video frames from a music video.

ClawHub Agent Skills author: Sellemain v0.7.1 MIT-0 3 files body ≈ 2 523 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 46/100 · Will not run — References files that are not bundled: examples/agent/AGENTS.md

ProcedureYouTubeMedia and videotype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
F
46/100
Will not run
References files that are not bundled: examples/agent/AGENTS.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: OpenClaw skill for using galdr's ARC workflow to turn YouTube URLs… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning missing-ref reference to a missing file: examples/agent/AGENTS.md

Process rating: all ten parameters 46/100

Will not run. References files that are not bundled: examples/agent/AGENTS.md
  • 0Tools and files. 1 referenced file(s) missing: examples/agent/AGENTS.md
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 3 mutating operations with no state check
  • 60Failures and branches. 2 branches
  • 85Steps. 56 steps, 1 vague phrases
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2523 tokens
  • low The response is described with custom markup (7 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
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 463: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 56 items
  • +4Has examples (12 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

External checks

ClawHub: clean
This skill appears to be a normal music-analysis helper, with expected network fetching, local output files, and optional model handoff disclosed well enough for its purpose.
LLM: benign (high) · VirusTotal: · 26 Aug 2026