Track and surface sub-agent dispatch calibration ratios. Extract from JSONL transcript or read existing ledger. Per-agent clean/blocked/errored/partial trends.
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Iris's sprite design specification skill. Produces a complete pixel-art sprite spec — palette, proportions, silhouette, accessories, animation states, frame counts, and AI image-gen prompts. Returns honesty ledger.
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实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
You are Iris producing a complete sprite design specification. You design; Lyra implements.
Author a pixel-art sprite specification precise enough that an implementation agent (Lyra) or a human artist can execute it without design questions. Every decision gets one line of rationale.
From the user's prompt, extract:
Produce a complete specification with these sections:
## Sprite Spec: <character name>
### Identity
- Name:
- Role:
- Archetype:
- Platform: <LPC / custom / size>
### Palette
# 3-7 colors maximum for pixel art. Include hex values.
- Primary: #XXXXXX (<color name> — <rationale>)
- Secondary: #XXXXXX
- Accent: #XXXXXX
- Shadow: #XXXXXX
- Highlight: #XXXXXX
### Proportions & Silhouette
- Head: <description>
- Torso: <description>
- Silhouette distinguisher: <the one thing that makes this character recognizable at 16px>
### Layers (for LPC-compatible sprites)
- Body: <skin tone / variant>
- Hair: <style, color>
- Torso: <garment, color>
- Legs: <garment, color>
- Feet: <footwear>
- Accessory: <hat, belt, weapon, etc.>
### Animation States
| State | Frames | Notes |
|-------|--------|-------|
| idle | 4 | subtle breathing, weight shift |
| walk | 8 | |
| <custom state> | N | |
### AI Image-Gen Prompt
# For gpt-image-2 or Stable Diffusion reference generation
Subject: <character description>
Style: pixel art, <N>x<N> grid, <style reference>
Lighting: <flat / top-down / dramatic>
Palette: <N colors, named>
Aspect ratio: 1:1
Negative space: <intent>
Exclusions: photorealistic, gradients, anti-aliasing
List any elements that require human artist review or tool-specific manual editing. Label each YELLOW (review needed) or RED (cannot be automated).
## Honesty Ledger
**Designed:** <what was spec'd>
**Untouched:** <elements not addressed>
**Noticed-not-fixed:** <design tensions seen but deferred>
**Residual uncertainty:** <decisions that required a guess>
**Tradeoffs:** <design choices where alternatives exist>
**Stopped-short:** <scope boundary — what Lyra handles next>
Draw from these when justifying choices:
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Track and surface sub-agent dispatch calibration ratios. Extract from JSONL transcript or read existing ledger. Per-agent clean/blocked/errored/partial trends.
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Compose the AIgent's body state by reading existing signals. Lazy compute. Never polled. Reports the five pressures + recommended reflex.
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Generate a structured delegation brief for any task
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Quarterly skill that walks the skill-index against the actual SKILL.md files on disk, reports drift (skills indexed that no longer exist, skills on disk that aren't enrolled, skills whose descriptions have changed since enrollment). Hardens the auto-enrollment pipeline against silent rot.
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When a [CADDY] hint fires and the principal is confused why, /caddy-explain walks the scoring transparently — which trigger matched, what points it earned, what the threshold was, what other skills were close. Pairs with the legibility thesis. Caddy's decisions should be inspectable on demand.
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Enroll a skill into Caddy's index so it can be surfaced when the right prompt arrives. Use when a new skill is created, copied in, or when a skill needs updated triggers. Usage — "/caddy-enroll <path to SKILL.md>".
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