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Constraint Specification

  • 254 installs
  • 153 repo stars
  • Updated June 9, 2026
  • owl-listener/ai-design-skills

Helps with ai & agent building tasks during AI-assisted development.

About

constraint-specification is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted coding.

  • constraint-specification
  • AI & Agent Building
  • AI-coding skill

Constraint Specification by the numbers

  • 254 all-time installs (skills.sh)
  • +42 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #2,538 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 4, 2026 (Skillselion catalog sync)
npx skills add https://github.com/owl-listener/ai-design-skills --skill constraint-specification

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Listed on Skillselion
Installs254
repo stars153
Last updatedJune 9, 2026
Repositoryowl-listener/ai-design-skills

What it does

Helps with ai & agent building tasks during AI-assisted development.

Files

SKILL.mdMarkdownGitHub ↗

Constraint Specification

Constraints are the rules that shape AI output — what format to use, how long to be, what to include, what to exclude. Well-specified constraints produce predictable, useful outputs. Vague constraints produce inconsistent results.

Types of Constraints

Format constraints:

  • Output structure (JSON, markdown, plain text, bullet points, prose)
  • Section headings and organisation
  • Required fields and optional fields
  • Data types and schemas

Length constraints:

  • Word count ranges (not exact numbers — models are bad at counting)
  • Section length proportions ("spend 60% on analysis, 40% on recommendations")
  • Minimum and maximum bounds
  • Conciseness directives ("be brief" vs. "be thorough")

Content constraints:

  • Topics to include and exclude
  • Required information elements
  • Prohibited content
  • Source restrictions (only use provided context, don't use external knowledge)

Tone constraints:

  • Formality level
  • Emotional register
  • Audience-appropriate language
  • Voice and style guidelines

Quality constraints:

  • Accuracy requirements ("cite sources", "flag uncertainty")
  • Completeness requirements ("address all aspects of the question")
  • Originality requirements ("don't repeat the question back")
  • Actionability requirements ("every recommendation must be implementable")

Writing Effective Constraints

  • Be specific: "Keep responses under 200 words" beats "be concise"
  • Prioritise: When constraints conflict, state which wins. "Accuracy over brevity."
  • Provide examples: Show what a constrained output looks like
  • Test boundaries: What happens at the edge of each constraint?
  • Separate hard and soft constraints: Hard constraints must always be met. Soft constraints are preferences.

Constraint Interactions

Constraints interact and can conflict:

  • "Be thorough" vs. "Keep it under 100 words"
  • "Be creative" vs. "Follow this exact format"
  • "Be helpful" vs. "Don't give medical advice"

Resolve conflicts explicitly in the prompt. Don't make the model guess which constraint takes priority.

Design Artefacts

  • Constraint specification documents per output type
  • Constraint priority hierarchies
  • Constraint test cases (inputs designed to stress each constraint)
  • Constraint violation examples (what bad looks like)
  • Constraint evolution logs (how constraints changed and why)

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