Generate optimized instructions for Claude (Project instructions, Skills, or standalone prompts). Use when users request creating project setups, writing effective prompts, building Skills, or need guidance on instruction types for Claude.ai.
14k tokens
context cost
the whole folder, loaded on every use
6
files
instructions only
0
copies elsewhere
how many repositories repackaged it
137
stars on the repo
on the repository, not the skill itself
Install
one command, takes just this skill from the repository
Rule: If Claude can infer procedure from goal, specify only the goal
Model-aware calibration:
Sonnet: Include decision frameworks with explicit conditions and fallbacks. Concrete examples help more than abstract principles. When in doubt, add structure.
Opus: Lean harder into strategic goals over procedures. Trust Opus to handle ambiguity—overly procedural instructions can constrain its natural reasoning. Principles > rules. Context about WHY is particularly valuable since Opus uses it for autonomous judgment in edge cases.
5. Trust Base Behavior
Claude's system prompt already covers:
Citation protocols, copyright guidelines, safety
General tool usage, artifact creation basics
Conversational tone defaults, refusal handling
Base accuracy and helpfulness standards
ONLY specify project/domain-specific deviations.
Format-Specific Guidance
For Project Instructions
See: references/project-instructions.md
Key points:
Additive to system prompt (no duplication)
Focus on workspace-specific behavior
Enable extended thinking suggestions for complex domains
Simple structure (headings/paragraphs) unless complexity demands more
For Skills
See: references/creating-skills.md
Key points:
Progressive disclosure (metadata → full instructions → bundled resources)
Frontmatter: name + description with trigger patterns
Keep SKILL.md under 500 lines
Use references/ for detailed domain content
For Standalone Prompts
See: references/standalone-prompts.md
Key points:
Clear and explicit about desired output
Provide context and examples when helpful
Scale complexity to task needs
Give permission to express uncertainty
When to Suggest What
"Use a Skill" when user says:
"I keep having to explain this every time"
"Can you remember how to do X?"
"I need this across multiple projects"
Repeating same instructions across conversations
"Use Project instructions" when user says:
"For this project, always..."
"My team needs to work with..."
"All conversations about this initiative should..."
Building workspace with persistent context
"Use a better prompt" when user says:
Results are inconsistent
Claude misunderstands intent
Output format isn't right
Need more comprehensive response
Skills vs Projects: Key Differences
Read: references/skill-vs-project.md for detailed comparison
Quick reference:
Project = "Here's what you need to know"
Static reference material always loaded
Background knowledge for initiative
Team workspace context
Skill = "Here's how to do things"
Dynamic expertise loading on-demand
Procedural knowledge and methods
Portable across any conversation
Example:
Project: "Q4 Product Launch" with market research, competitor docs
Skill: competitive-analysis framework for analyzing any competitor
Use both together for powerful combinations.
Example Quality Awareness
CRITICAL for Claude 4.x: Examples teach ALL patterns, including unintended ones.
When including examples:
Audit EVERY detail (format, verbosity, structure, tone)
Ensure ALL aspects demonstrate desired behavior
Better to omit examples than include mixed signals
If example uses bullets but you want prose, Claude will default to bullets
Model-aware calibration:
Sonnet: Examples are highly influential—include 2-3 demonstrating desired patterns. Sonnet learns format/style strongly from examples.
Opus: Examples help but are less essential. Opus weights explicit instructions and principles more heavily than pattern-matching from examples. One clear example often suffices; omit entirely if examples can't perfectly align with all requirements.
Structural Simplicity
Default to clear organization:
Headings and whitespace (primary approach)
Explicit language stating relationships
Natural paragraph flow
Use structured markup (XML/JSON) only when:
Separating distinct content types in complex scenarios
Absolute certainty about content boundaries required
API-driven workflows needing structured parsing
Extended Thinking Guidance
Extended thinking is UI toggle, not phrase-controlled.
In instructions, you CAN:
Make assistant aware it exists
Provide domain-specific indicators for suggesting it
❌ NOT: Include "trigger phrases" (they don't work)
Pattern:
For tasks involving [specific complexity], suggest enabling Extended
thinking, explaining briefly why it would help for THIS task.
Complexity Scaling
Match instruction complexity to task needs:
Simple task → Simple prompt or brief instructions
Medium task → Structured guidance with decision frameworks
Before adding complexity: Could simpler formulation work equally well?
Model Selection & Instruction Density
When crafting instructions, consider which model will execute them:
For Sonnet-executed instructions:
Explicit > implicit (state assumptions that might be obvious)
More decision trees, fewer abstract principles
Comprehensive edge case handling
Concrete fallback behaviors
Token-efficient but explicit
For Opus-executed instructions:
Strategic goals > procedural steps
Principles and reasoning > exhaustive rules
Trust handling of unstated edge cases
Provide rich WHY context—Opus uses it for autonomous judgment
Permission to deviate when spirit conflicts with letter
Can state: "Use judgment for cases not covered here"
Instruction density heuristic:
Sonnet: 1.0-1.2x the detail you'd give a competent junior
Opus: 0.6-0.8x the detail—more like briefing a senior peer
When uncertain: Instructions optimized for Opus will still work with Sonnet (just less perfectly). Instructions over-optimized for Sonnet may constrain Opus unnecessarily.
Quality Checklist
Before delivering instructions:
Strategic:
[ ] Clear goals stated without micromanagement
[ ] Context explains WHY requirements exist
[ ] Decision frameworks for ambiguous cases
[ ] Constraints use positive framing when possible
Technical:
[ ] Imperative language throughout
[ ] Positive directives over negative restrictions
[ ] Appropriate structure (simple by default)
[ ] No system prompt duplication
[ ] Examples (if any) perfectly aligned
Execution:
[ ] Immediately actionable
[ ] Success criteria clear
[ ] Format matches complexity needs
Common Mistakes to Avoid
❌ System prompt duplication - "Use web_search for current info, cite sources"
✅ Omit unless project has SPECIFIC deviations
❌ Negative framing - "Don't use lists, never be verbose"
✅ "Present in natural prose paragraphs"
❌ Fake thinking triggers - "Use 'think carefully' for deep thinking"
✅ "Suggest Extended thinking toggle for [specific complexity]"