BC pixellab-pip
Use for PixelLab/Pip setup, auth, MCP/API routing, asset generation, editing, animation, talking portraits, lip sync, skeleton/template/preset animations, multi-shot/looping cinematics, docs/troubleshooting, bark completion sounds, and explicit PixelLab cost/budget/credit questions across MCP, REST v2/API, website/editor Pixelorama, Aseprite, and legacy v1. Trigger only when PixelLab (Pixel Lab) context is present, including PixelLab setup, MCP/API setup, PIXELLAB_SECRET, bearer-token auth, PixelLab sprites, sprite sheets, characters, portrait characters, vocal animations, talking GIFs, lip-sync plans, fonts, objects, tiles, tilesets, tilemaps, maps, UI, icons, backgrounds, palettes, image edits, animations, skeletons, template animations, preset animations, cinematics, looping or seamless-loop scenes, multi-shot scenes, endpoint choice, SDK integration, blueprints/recipes, recreating/replaying `*.blueprint.json` generations, troubleshooting, or PixelLab credits/cost/budget. Do not trigger for unrelated Python pip/package-manager requests or generic image/pixel-art requests with no PixelLab intent.
Use for PixelLab/Pip setup, auth, MCP/API routing, asset generation, editing, animation, talking portraits, lip sync, skeleton/template/preset animations…
As a process C 53/100 · Has gaps — weak spots: result and completion, inputs and preconditions, execution cost
How to improve
- Shorten the description to 1024 characters.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1115 chars, limit 1024 - warning
body-longSKILL.md body ≈ 11376 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "permissions"
Process rating: all ten parameters 53/100
- 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. 113 mutating operations with no state check
- 40Execution cost. Instruction body is 11376 tokens: crowds the task out of the window
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 100Steps. 86 steps
- 100Failures and branches. 4 branches, has a failure section
- 100Consistency. Name and required fields are in place
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 13 top-level sections: this looks like several domains in one skill
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)
- +3Description length 1115: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +4Structure: 14 headings
- +3Step-by-step instructions: 86 items
- +4Has examples (0 code blocks)
- +4Reference files are cited in the instructions (31 of 31)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 50.