CC subwave-log-analysis
Analyse the SUB/WAVE radio station's unified event log (state/logs/events-*.jsonl) and give the operator a diagnostic report on how the station is behaving — Navidrome/ Subsonic API call patterns, the DJ picker's behaviour and music-library coverage, and runtime health anomalies. Use this skill whenever the user wants to understand or get feedback on what the radio is doing under the hood: how Navidrome calls are being made and how often, why the picker keeps choosing certain tracks or artists, whether the library pool is too narrow, whether traces are failing or running slow, or asks things like "analyse the subwave logs", "check the radio's behaviour", "what is the picker doing", "why does it keep playing the same artists", "is the station healthy", "how are the navidrome calls looking", "give me feedback on the event log". Trigger this skill even if the user does not name the log file or the script — any request to diagnose, audit, review, or get feedback on SUB/WAVE's runtime behaviour from its logs belongs here.
Promises to parse SUB/WAVE radio logs: API call frequency to Navidrome, why the picker selects certain tracks, library coverage gaps. Files are intact, but the description cuts off—no clarity on what the skill actually extracts from events or how it interprets them. Code passed baseline checks (no critical errors), yet quality score 64 and process score 61 hint at analysis logic gaps. Linter complains about description length and formatting. No model runs or sandbox tests.
Install if your radio station is live with accumulated logs. Expect raw output—detailed conclusions about picker behaviour or library bottlenecks may not materialise. Needs description polish and real-data testing before production use.
Analyse the SUB/WAVE radio station's unified event log (state/logs/events-.jsonl) and give the operator a diagnostic report on how the station is behaving —…
As a process C 61/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- Shorten the description to 1024 characters.
- 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1032 chars, limit 1024
Process rating: all ten parameters 61/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 2 mutating operations with no state check
- 60Tools and files. Uses tools (web, node) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 24 steps
- 100Failures and branches. 3 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2590 tokens
- 100Progress reporting. Reports progress
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 1032: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 7 example trigger phrases
- +4Structure: 10 headings
- +3Step-by-step instructions: 24 items
- +4Has examples (2 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.