Prompt optimize

Skill senda-labs/DQIII8/.claude/skills/prompt-optimize

Analyze and optimize a prompt for the DQIII8 ecosystem. Classifies prompt type (LLM routing, image gen, TTS, agent instruction, Telegram), scores 5 dimensions, produces optimized version.From its SKILL.md

Install

npx -y skills add senda-labs/DQIII8 --skill prompt-optimize

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One thing to look at

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SKILL.md

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/prompt-optimize — Optimize a Prompt for DQIII8/Pipeline

Analyze and optimize a prompt for maximum effectiveness in the DQIII8 ecosystem (LLM routing, scene director, TTS, Telegram bot, or agent instructions).

Usage

/prompt-optimize [the prompt text or file path]

Your Task

Given the prompt in $ARGUMENTS:

1. Classify the prompt type

LLM routing prompt (sent to Ollama/Groq/Claude)
Image generation prompt (sent to fal.ai flux-general)
TTS prompt (narration text for ElevenLabs)
Agent instruction (agent .md system prompt)
Telegram bot message (user-facing output)

2. Evaluate on 5 dimensions (score 0-10 each)

Dimension	What to check
Clarity	Unambiguous intent, no vague instructions
Specificity	Concrete examples, exact formats, numbers
Conciseness	No filler words, no redundant instructions
Output contract	Explicit format (JSON/markdown/text) stated
Edge cases	Handles empty input, failure, ambiguity

3. Produce optimized version

Apply these DQIII8-specific improvements:

For LLM prompts:

Add Output ONLY JSON (no markdown): if structured output needed
Include exact field names in the output contract
State the model tier this will run on (Haiku/Sonnet/Groq)

For image prompts (fal.ai):

Lead with cinematographer style reference
Include shot_type + camera_angle early in the prompt
End with no text no watermarks no logos
Keep under 200 tokens

For TTS narration:

Present tense, max 8 words per sentence
Include YOU/YOUR in at least 1 sentence
Start with a specific name, date, or number
Never start with "In [year]" / "During" / "Throughout"

For agent instructions:

Add ## When NOT to use section if missing
Verify trigger keywords match CLAUDE.md delegation table
Confirm model assignment matches the canonical C/B/B+/B++/A/S tier table (.claude/rules/03_tiering_and_routing.md)

For Telegram messages:

Keep under 280 chars for readability
Use *bold* for key metrics, `code` for commands
No raw paths longer than 40 chars

4. Output format

PROMPT OPTIMIZATION REPORT
===========================
Type: [classified type]
Original score: [X]/50

Scores:
  Clarity:       [X]/10  — [one-line finding]
  Specificity:   [X]/10  — [one-line finding]
  Conciseness:   [X]/10  — [one-line finding]
  Output contract:[X]/10 — [one-line finding]
  Edge cases:    [X]/10  — [one-line finding]

Key issues:
  1. [issue + fix]
  2. [issue + fix]

Optimized prompt:
---
[full optimized prompt text]
---
Optimized score: [X]/50

CRITICAL

Do NOT change the semantic intent of the prompt
Do NOT add hallucinated constraints (only what the system actually supports)
Do NOT optimize for a different model tier than the one specified
If the prompt is already >=40/50 → report PASS with minor suggestions only

User Input

$ARGUMENTS