Add personal superpowers overlay system

Enables users to write and manage their own skills alongside core skills.

## Key Features:
- Auto-setup on first session: Creates ~/.config/superpowers/ git repo
- Two-tier skills: Personal skills shadow core skills when paths match
- Environment variable support: PERSONAL_SUPERPOWERS_DIR, XDG_CONFIG_HOME
- GitHub integration: Optional public repo creation for sharing skills
- CLI-agnostic: Works across Claude Code, Codex CLI, Gemini CLI (future)

## Changes:
- Added hooks/setup-personal-superpowers.sh - Auto-initializes personal repo
- Updated hooks/session-start.sh - Runs setup, offers GitHub repo creation
- Updated list-skills, skills-search - Search both personal and core skills
- Renamed skills/meta/creating-skills → writing-skills
- Added skills/meta/setting-up-personal-superpowers - Setup documentation
- Added skills/meta/sharing-skills - Contribution workflow
- Removed skills/meta/installing-skills - Old ~/.clank system
- Removed all INDEX.md files - Replaced by list-skills tool
- Updated README.md, getting-started - Document personal skills workflow

## Architecture:
~/.config/superpowers/skills/  # Personal (user-created, git-tracked)
${CLAUDE_PLUGIN_ROOT}/skills/  # Core (read-only, from plugin)

Search order: Personal first, core second (first match wins)
This commit is contained in:
Jesse Vincent
2025-10-10 14:01:45 -07:00
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---
name: Creating Skills
description: TDD for process documentation - test with subagents before writing, iterate until bulletproof
when_to_use: When you discover a technique, pattern, or tool worth documenting for reuse. When editing existing skills. When asked to modify skill documentation. When you've written a skill and need to verify it works before deploying.
version: 4.1.0
languages: all
---
# Creating Skills
## Overview
**Creating skills IS Test-Driven Development applied to process documentation.**
You write test cases (pressure scenarios with subagents), watch them fail (baseline behavior), write the skill (documentation), watch tests pass (agents comply), and refactor (close loopholes).
**Core principle:** If you didn't watch an agent fail without the skill, you don't know if the skill teaches the right thing.
See skills/testing/test-driven-development for the fundamental RED-GREEN-REFACTOR cycle. This skill adapts TDD to documentation.
## What is a Skill?
A **skill** is a reference guide for proven techniques, patterns, or tools. Skills help future Claude instances find and apply effective approaches.
**Skills are:** Reusable techniques, patterns, tools, reference guides
**Skills are NOT:** Narratives about how you solved a problem once
## TDD Mapping for Skills
| TDD Concept | Skill Creation |
|-------------|----------------|
| **Test case** | Pressure scenario with subagent |
| **Production code** | Skill document (SKILL.md) |
| **Test fails (RED)** | Agent violates rule without skill (baseline) |
| **Test passes (GREEN)** | Agent complies with skill present |
| **Refactor** | Close loopholes while maintaining compliance |
| **Write test first** | Run baseline scenario BEFORE writing skill |
| **Watch it fail** | Document exact rationalizations agent uses |
| **Minimal code** | Write skill addressing those specific violations |
| **Watch it pass** | Verify agent now complies |
| **Refactor cycle** | Find new rationalizations → plug → re-verify |
The entire skill creation process follows RED-GREEN-REFACTOR.
## When to Create a Skill
**Create when:**
- Technique wasn't intuitively obvious to you
- You'd reference this again across projects
- Pattern applies broadly (not project-specific)
- Others would benefit
**Don't create for:**
- One-off solutions
- Standard practices well-documented elsewhere
- Project-specific conventions (put in CLAUDE.md)
## Skill Types
### Technique
Concrete method with steps to follow (condition-based-waiting, root-cause-tracing)
### Pattern
Way of thinking about problems (flatten-with-flags, test-invariants)
### Reference
API docs, syntax guides, tool documentation (office docs)
## Directory Structure
```
skills/
skill-name/
SKILL.md # Main reference (required)
supporting-file.* # Only if needed
```
**Flat namespace** - all skills in one searchable location
**Separate files for:**
1. **Heavy reference** (100+ lines) - API docs, comprehensive syntax
2. **Reusable tools** - Scripts, utilities, templates
**Keep inline:**
- Principles and concepts
- Code patterns (< 50 lines)
- Everything else
## SKILL.md Structure
```markdown
---
name: Human-Readable Name
description: One-line summary of what this does
when_to_use: Symptoms and situations when you need this (CSO-critical)
version: 1.0.0
languages: all | [typescript, python] | etc
dependencies: (optional) Required tools/libraries
---
# Skill Name
## Overview
What is this? Core principle in 1-2 sentences.
## When to Use
[Small inline flowchart IF decision non-obvious]
Bullet list with SYMPTOMS and use cases
When NOT to use
## Core Pattern (for techniques/patterns)
Before/after code comparison
## Quick Reference
Table or bullets for scanning common operations
## Implementation
Inline code for simple patterns
@link to file for heavy reference or reusable tools
## Common Mistakes
What goes wrong + fixes
## Real-World Impact (optional)
Concrete results
```
## Claude Search Optimization (CSO)
**Critical for discovery:** Future Claude needs to FIND your skill
### 1. Rich when_to_use
Include SYMPTOMS not just abstract use cases:
```yaml
# ❌ BAD: Too abstract
when_to_use: For async testing
# ✅ GOOD: Symptoms and context
when_to_use: When tests use setTimeout/sleep and are flaky, timing-dependent,
pass locally but fail in CI, or timeout when run in parallel
```
### 2. Keyword Coverage
Use words Claude would search for:
- Error messages: "Hook timed out", "ENOTEMPTY", "race condition"
- Symptoms: "flaky", "hanging", "zombie", "pollution"
- Synonyms: "timeout/hang/freeze", "cleanup/teardown/afterEach"
- Tools: Actual commands, library names, file types
### 3. Descriptive Naming
**Use active voice, verb-first:**
-`creating-skills` not `skill-creation`
-`testing-skills-with-subagents` not `subagent-skill-testing`
### 4. Token Efficiency (Critical)
**Problem:** getting-started and frequently-referenced skills load into EVERY conversation. Every token counts.
**Target word counts:**
- getting-started workflows: <150 words each
- Frequently-loaded skills: <200 words total
- Other skills: <500 words (still be concise)
**Techniques:**
**Move details to tool help:**
```bash
# ❌ BAD: Document all flags in SKILL.md
search-conversations supports --text, --both, --after DATE, --before DATE, --limit N
# ✅ GOOD: Reference --help
search-conversations supports multiple modes and filters. Run --help for details.
```
**Use cross-references:**
```markdown
# ❌ BAD: Repeat workflow details
When searching, dispatch subagent with template...
[20 lines of repeated instructions]
# ✅ GOOD: Reference other skill
Always use subagents (50-100x context savings). See skills/getting-started for workflow.
```
**Compress examples:**
```markdown
# ❌ BAD: Verbose example (42 words)
your human partner: "How did we handle authentication errors in React Router before?"
You: I'll search past conversations for React Router authentication patterns.
[Dispatch subagent with search query: "React Router authentication error handling 401"]
# ✅ GOOD: Minimal example (20 words)
Partner: "How did we handle auth errors in React Router?"
You: Searching...
[Dispatch subagent → synthesis]
```
**Eliminate redundancy:**
- Don't repeat what's in cross-referenced skills
- Don't explain what's obvious from command
- Don't include multiple examples of same pattern
**Verification:**
```bash
wc -w skills/path/SKILL.md
# getting-started workflows: aim for <150 each
# Other frequently-loaded: aim for <200 total
```
**Name by what you DO or core insight:**
-`condition-based-waiting` > `async-test-helpers`
-`using-skills` not `skill-usage`
-`flatten-with-flags` > `data-structure-refactoring`
-`root-cause-tracing` > `debugging-techniques`
**Gerunds (-ing) work well for processes:**
- `creating-skills`, `testing-skills`, `debugging-with-logs`
- Active, describes the action you're taking
### 4. Content Repetition
Mention key concepts multiple times:
- In description
- In when_to_use
- In overview
- In section headers
Grep hits from multiple places = easier discovery
## Flowchart Usage
```dot
digraph when_flowchart {
"Need to show information?" [shape=diamond];
"Decision where I might go wrong?" [shape=diamond];
"Use markdown" [shape=box];
"Small inline flowchart" [shape=box];
"Need to show information?" -> "Decision where I might go wrong?" [label="yes"];
"Decision where I might go wrong?" -> "Small inline flowchart" [label="yes"];
"Decision where I might go wrong?" -> "Use markdown" [label="no"];
}
```
**Use flowcharts ONLY for:**
- Non-obvious decision points
- Process loops where you might stop too early
- "When to use A vs B" decisions
**Never use flowcharts for:**
- Reference material → Tables, lists
- Code examples → Markdown blocks
- Linear instructions → Numbered lists
- Labels without semantic meaning (step1, helper2)
See @graphviz-conventions.dot for graphviz style rules.
## Code Examples
**One excellent example beats many mediocre ones**
Choose most relevant language:
- Testing techniques → TypeScript/JavaScript
- System debugging → Shell/Python
- Data processing → Python
**Good example:**
- Complete and runnable
- Well-commented explaining WHY
- From real scenario
- Shows pattern clearly
- Ready to adapt (not generic template)
**Don't:**
- Implement in 5+ languages
- Create fill-in-the-blank templates
- Write contrived examples
You're good at porting - one great example is enough.
## File Organization
### Self-Contained Skill
```
defense-in-depth/
SKILL.md # Everything inline
```
When: All content fits, no heavy reference needed
### Skill with Reusable Tool
```
condition-based-waiting/
SKILL.md # Overview + patterns
example.ts # Working helpers to adapt
```
When: Tool is reusable code, not just narrative
### Skill with Heavy Reference
```
pptx/
SKILL.md # Overview + workflows
pptxgenjs.md # 600 lines API reference
ooxml.md # 500 lines XML structure
scripts/ # Executable tools
```
When: Reference material too large for inline
## The Iron Law (Same as TDD)
```
NO SKILL WITHOUT A FAILING TEST FIRST
```
This applies to NEW skills AND EDITS to existing skills.
Write skill before testing? Delete it. Start over.
Edit skill without testing? Same violation.
**No exceptions:**
- Not for "simple additions"
- Not for "just adding a section"
- Not for "documentation updates"
- Don't keep untested changes as "reference"
- Don't "adapt" while running tests
- Delete means delete
See skills/testing/test-driven-development for why this matters. Same principles apply to documentation.
## Testing All Skill Types
Different skill types need different test approaches:
### Discipline-Enforcing Skills (rules/requirements)
**Examples:** TDD, verification-before-completion, designing-before-coding
**Test with:**
- Academic questions: Do they understand the rules?
- Pressure scenarios: Do they comply under stress?
- Multiple pressures combined: time + sunk cost + exhaustion
- Identify rationalizations and add explicit counters
**Success criteria:** Agent follows rule under maximum pressure
### Technique Skills (how-to guides)
**Examples:** condition-based-waiting, root-cause-tracing, defensive-programming
**Test with:**
- Application scenarios: Can they apply the technique correctly?
- Variation scenarios: Do they handle edge cases?
- Missing information tests: Do instructions have gaps?
**Success criteria:** Agent successfully applies technique to new scenario
### Pattern Skills (mental models)
**Examples:** reducing-complexity, information-hiding concepts
**Test with:**
- Recognition scenarios: Do they recognize when pattern applies?
- Application scenarios: Can they use the mental model?
- Counter-examples: Do they know when NOT to apply?
**Success criteria:** Agent correctly identifies when/how to apply pattern
### Reference Skills (documentation/APIs)
**Examples:** API documentation, command references, library guides
**Test with:**
- Retrieval scenarios: Can they find the right information?
- Application scenarios: Can they use what they found correctly?
- Gap testing: Are common use cases covered?
**Success criteria:** Agent finds and correctly applies reference information
## Common Rationalizations for Skipping Testing
| Excuse | Reality |
|--------|---------|
| "Skill is obviously clear" | Clear to you ≠ clear to other agents. Test it. |
| "It's just a reference" | References can have gaps, unclear sections. Test retrieval. |
| "Testing is overkill" | Untested skills have issues. Always. 15 min testing saves hours. |
| "I'll test if problems emerge" | Problems = agents can't use skill. Test BEFORE deploying. |
| "Too tedious to test" | Testing is less tedious than debugging bad skill in production. |
| "I'm confident it's good" | Overconfidence guarantees issues. Test anyway. |
| "Academic review is enough" | Reading ≠ using. Test application scenarios. |
| "No time to test" | Deploying untested skill wastes more time fixing it later. |
**All of these mean: Test before deploying. No exceptions.**
## Bulletproofing Skills Against Rationalization
Skills that enforce discipline (like TDD) need to resist rationalization. Agents are smart and will find loopholes when under pressure.
**Psychology note:** Understanding WHY persuasion techniques work helps you apply them systematically. See persuasion-principles.md for research foundation (Cialdini, 2021; Meincke et al., 2025) on authority, commitment, scarcity, social proof, and unity principles.
### Close Every Loophole Explicitly
Don't just state the rule - forbid specific workarounds:
<Bad>
```markdown
Write code before test? Delete it.
```
</Bad>
<Good>
```markdown
Write code before test? Delete it. Start over.
**No exceptions:**
- Don't keep it as "reference"
- Don't "adapt" it while writing tests
- Don't look at it
- Delete means delete
```
</Good>
### Address "Spirit vs Letter" Arguments
Add foundational principle early:
```markdown
**Violating the letter of the rules is violating the spirit of the rules.**
```
This cuts off entire class of "I'm following the spirit" rationalizations.
### Build Rationalization Table
Capture rationalizations from baseline testing (see Testing section below). Every excuse agents make goes in the table:
```markdown
| Excuse | Reality |
|--------|---------|
| "Too simple to test" | Simple code breaks. Test takes 30 seconds. |
| "I'll test after" | Tests passing immediately prove nothing. |
| "Tests after achieve same goals" | Tests-after = "what does this do?" Tests-first = "what should this do?" |
```
### Create Red Flags List
Make it easy for agents to self-check when rationalizing:
```markdown
## Red Flags - STOP and Start Over
- Code before test
- "I already manually tested it"
- "Tests after achieve the same purpose"
- "It's about spirit not ritual"
- "This is different because..."
**All of these mean: Delete code. Start over with TDD.**
```
### Update CSO for Violation Symptoms
Add to when_to_use: symptoms of when you're ABOUT to violate the rule:
```yaml
when_to_use: Every feature and bugfix. When you wrote code before tests.
When you're tempted to test after. When manually testing seems faster.
```
## RED-GREEN-REFACTOR for Skills
Follow the TDD cycle:
### RED: Write Failing Test (Baseline)
Run pressure scenario with subagent WITHOUT the skill. Document exact behavior:
- What choices did they make?
- What rationalizations did they use (verbatim)?
- Which pressures triggered violations?
This is "watch the test fail" - you must see what agents naturally do before writing the skill.
### GREEN: Write Minimal Skill
Write skill that addresses those specific rationalizations. Don't add extra content for hypothetical cases.
Run same scenarios WITH skill. Agent should now comply.
### REFACTOR: Close Loopholes
Agent found new rationalization? Add explicit counter. Re-test until bulletproof.
**See skills/testing-skills-with-subagents for:**
- How to write pressure scenarios
- Pressure types (time, sunk cost, authority, exhaustion)
- Plugging holes systematically
- Meta-testing techniques
## Anti-Patterns
### ❌ Narrative Example
"In session 2025-10-03, we found empty projectDir caused..."
**Why bad:** Too specific, not reusable
### ❌ Multi-Language Dilution
example-js.js, example-py.py, example-go.go
**Why bad:** Mediocre quality, maintenance burden
### ❌ Code in Flowcharts
```dot
step1 [label="import fs"];
step2 [label="read file"];
```
**Why bad:** Can't copy-paste, hard to read
### ❌ Generic Labels
helper1, helper2, step3, pattern4
**Why bad:** Labels should have semantic meaning
## STOP: Before Moving to Next Skill
**After writing ANY skill, you MUST STOP and complete the deployment process.**
**Do NOT:**
- Create multiple skills in batch without testing each
- Update INDEX.md before testing skills
- Move to next skill before current one is verified
- Skip testing because "batching is more efficient"
**The deployment checklist below is MANDATORY for EACH skill.**
Deploying untested skills = deploying untested code. It's a violation of quality standards.
## Skill Creation Checklist (TDD Adapted)
**IMPORTANT: Use TodoWrite to create todos for EACH checklist item below.**
**RED Phase - Write Failing Test:**
- [ ] Create pressure scenarios (3+ combined pressures for discipline skills)
- [ ] Run scenarios WITHOUT skill - document baseline behavior verbatim
- [ ] Identify patterns in rationalizations/failures
**GREEN Phase - Write Minimal Skill:**
- [ ] Name describes what you DO or core insight
- [ ] YAML frontmatter with rich when_to_use (include symptoms!)
- [ ] Keywords throughout for search (errors, symptoms, tools)
- [ ] Clear overview with core principle
- [ ] Address specific baseline failures identified in RED
- [ ] Code inline OR @link to separate file
- [ ] One excellent example (not multi-language)
- [ ] Run scenarios WITH skill - verify agents now comply
**REFACTOR Phase - Close Loopholes:**
- [ ] Identify NEW rationalizations from testing
- [ ] Add explicit counters (if discipline skill)
- [ ] Build rationalization table from all test iterations
- [ ] Create red flags list
- [ ] Re-test until bulletproof
**Quality Checks:**
- [ ] Small flowchart only if decision non-obvious
- [ ] Quick reference table
- [ ] Common mistakes section
- [ ] No narrative storytelling
- [ ] Supporting files only for tools or heavy reference
## Discovery Workflow
How future Claude finds your skill:
1. **Encounters problem** ("tests are flaky")
2. **Greps skills** (`grep -r "flaky" ~/.claude/skills/`)
3. **Finds SKILL.md** (rich when_to_use matches)
4. **Scans overview** (is this relevant?)
5. **Reads patterns** (quick reference table)
6. **Loads example** (only when implementing)
**Optimize for this flow** - put searchable terms early and often.
## The Bottom Line
**Creating skills IS TDD for process documentation.**
Same Iron Law: No skill without failing test first.
Same cycle: RED (baseline) → GREEN (write skill) → REFACTOR (close loopholes).
Same benefits: Better quality, fewer surprises, bulletproof results.
If you follow TDD for code, follow it for skills. It's the same discipline applied to documentation.

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digraph STYLE_GUIDE {
// The style guide for our process DSL, written in the DSL itself
// Node type examples with their shapes
subgraph cluster_node_types {
label="NODE TYPES AND SHAPES";
// Questions are diamonds
"Is this a question?" [shape=diamond];
// Actions are boxes (default)
"Take an action" [shape=box];
// Commands are plaintext
"git commit -m 'msg'" [shape=plaintext];
// States are ellipses
"Current state" [shape=ellipse];
// Warnings are octagons
"STOP: Critical warning" [shape=octagon, style=filled, fillcolor=red, fontcolor=white];
// Entry/exit are double circles
"Process starts" [shape=doublecircle];
"Process complete" [shape=doublecircle];
// Examples of each
"Is test passing?" [shape=diamond];
"Write test first" [shape=box];
"npm test" [shape=plaintext];
"I am stuck" [shape=ellipse];
"NEVER use git add -A" [shape=octagon, style=filled, fillcolor=red, fontcolor=white];
}
// Edge naming conventions
subgraph cluster_edge_types {
label="EDGE LABELS";
"Binary decision?" [shape=diamond];
"Yes path" [shape=box];
"No path" [shape=box];
"Binary decision?" -> "Yes path" [label="yes"];
"Binary decision?" -> "No path" [label="no"];
"Multiple choice?" [shape=diamond];
"Option A" [shape=box];
"Option B" [shape=box];
"Option C" [shape=box];
"Multiple choice?" -> "Option A" [label="condition A"];
"Multiple choice?" -> "Option B" [label="condition B"];
"Multiple choice?" -> "Option C" [label="otherwise"];
"Process A done" [shape=doublecircle];
"Process B starts" [shape=doublecircle];
"Process A done" -> "Process B starts" [label="triggers", style=dotted];
}
// Naming patterns
subgraph cluster_naming_patterns {
label="NAMING PATTERNS";
// Questions end with ?
"Should I do X?";
"Can this be Y?";
"Is Z true?";
"Have I done W?";
// Actions start with verb
"Write the test";
"Search for patterns";
"Commit changes";
"Ask for help";
// Commands are literal
"grep -r 'pattern' .";
"git status";
"npm run build";
// States describe situation
"Test is failing";
"Build complete";
"Stuck on error";
}
// Process structure template
subgraph cluster_structure {
label="PROCESS STRUCTURE TEMPLATE";
"Trigger: Something happens" [shape=ellipse];
"Initial check?" [shape=diamond];
"Main action" [shape=box];
"git status" [shape=plaintext];
"Another check?" [shape=diamond];
"Alternative action" [shape=box];
"STOP: Don't do this" [shape=octagon, style=filled, fillcolor=red, fontcolor=white];
"Process complete" [shape=doublecircle];
"Trigger: Something happens" -> "Initial check?";
"Initial check?" -> "Main action" [label="yes"];
"Initial check?" -> "Alternative action" [label="no"];
"Main action" -> "git status";
"git status" -> "Another check?";
"Another check?" -> "Process complete" [label="ok"];
"Another check?" -> "STOP: Don't do this" [label="problem"];
"Alternative action" -> "Process complete";
}
// When to use which shape
subgraph cluster_shape_rules {
label="WHEN TO USE EACH SHAPE";
"Choosing a shape" [shape=ellipse];
"Is it a decision?" [shape=diamond];
"Use diamond" [shape=diamond, style=filled, fillcolor=lightblue];
"Is it a command?" [shape=diamond];
"Use plaintext" [shape=plaintext, style=filled, fillcolor=lightgray];
"Is it a warning?" [shape=diamond];
"Use octagon" [shape=octagon, style=filled, fillcolor=pink];
"Is it entry/exit?" [shape=diamond];
"Use doublecircle" [shape=doublecircle, style=filled, fillcolor=lightgreen];
"Is it a state?" [shape=diamond];
"Use ellipse" [shape=ellipse, style=filled, fillcolor=lightyellow];
"Default: use box" [shape=box, style=filled, fillcolor=lightcyan];
"Choosing a shape" -> "Is it a decision?";
"Is it a decision?" -> "Use diamond" [label="yes"];
"Is it a decision?" -> "Is it a command?" [label="no"];
"Is it a command?" -> "Use plaintext" [label="yes"];
"Is it a command?" -> "Is it a warning?" [label="no"];
"Is it a warning?" -> "Use octagon" [label="yes"];
"Is it a warning?" -> "Is it entry/exit?" [label="no"];
"Is it entry/exit?" -> "Use doublecircle" [label="yes"];
"Is it entry/exit?" -> "Is it a state?" [label="no"];
"Is it a state?" -> "Use ellipse" [label="yes"];
"Is it a state?" -> "Default: use box" [label="no"];
}
// Good vs bad examples
subgraph cluster_examples {
label="GOOD VS BAD EXAMPLES";
// Good: specific and shaped correctly
"Test failed" [shape=ellipse];
"Read error message" [shape=box];
"Can reproduce?" [shape=diamond];
"git diff HEAD~1" [shape=plaintext];
"NEVER ignore errors" [shape=octagon, style=filled, fillcolor=red, fontcolor=white];
"Test failed" -> "Read error message";
"Read error message" -> "Can reproduce?";
"Can reproduce?" -> "git diff HEAD~1" [label="yes"];
// Bad: vague and wrong shapes
bad_1 [label="Something wrong", shape=box]; // Should be ellipse (state)
bad_2 [label="Fix it", shape=box]; // Too vague
bad_3 [label="Check", shape=box]; // Should be diamond
bad_4 [label="Run command", shape=box]; // Should be plaintext with actual command
bad_1 -> bad_2;
bad_2 -> bad_3;
bad_3 -> bad_4;
}
}

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# Persuasion Principles for Skill Design
## Overview
LLMs respond to the same persuasion principles as humans. Understanding this psychology helps you design more effective skills - not to manipulate, but to ensure critical practices are followed even under pressure.
**Research foundation:** Meincke et al. (2025) tested 7 persuasion principles with N=28,000 AI conversations. Persuasion techniques more than doubled compliance rates (33% → 72%, p < .001).
## The Seven Principles
### 1. Authority
**What it is:** Deference to expertise, credentials, or official sources.
**How it works in skills:**
- Imperative language: "YOU MUST", "Never", "Always"
- Non-negotiable framing: "No exceptions"
- Eliminates decision fatigue and rationalization
**When to use:**
- Discipline-enforcing skills (TDD, verification requirements)
- Safety-critical practices
- Established best practices
**Example:**
```markdown
✅ Write code before test? Delete it. Start over. No exceptions.
❌ Consider writing tests first when feasible.
```
### 2. Commitment
**What it is:** Consistency with prior actions, statements, or public declarations.
**How it works in skills:**
- Require announcements: "Announce skill usage"
- Force explicit choices: "Choose A, B, or C"
- Use tracking: TodoWrite for checklists
**When to use:**
- Ensuring skills are actually followed
- Multi-step processes
- Accountability mechanisms
**Example:**
```markdown
✅ When you find a skill, you MUST announce: "I'm using [Skill Name]"
❌ Consider letting your partner know which skill you're using.
```
### 3. Scarcity
**What it is:** Urgency from time limits or limited availability.
**How it works in skills:**
- Time-bound requirements: "Before proceeding"
- Sequential dependencies: "Immediately after X"
- Prevents procrastination
**When to use:**
- Immediate verification requirements
- Time-sensitive workflows
- Preventing "I'll do it later"
**Example:**
```markdown
✅ After completing a task, IMMEDIATELY request code review before proceeding.
❌ You can review code when convenient.
```
### 4. Social Proof
**What it is:** Conformity to what others do or what's considered normal.
**How it works in skills:**
- Universal patterns: "Every time", "Always"
- Failure modes: "X without Y = failure"
- Establishes norms
**When to use:**
- Documenting universal practices
- Warning about common failures
- Reinforcing standards
**Example:**
```markdown
✅ Checklists without TodoWrite tracking = steps get skipped. Every time.
❌ Some people find TodoWrite helpful for checklists.
```
### 5. Unity
**What it is:** Shared identity, "we-ness", in-group belonging.
**How it works in skills:**
- Collaborative language: "our codebase", "we're colleagues"
- Shared goals: "we both want quality"
**When to use:**
- Collaborative workflows
- Establishing team culture
- Non-hierarchical practices
**Example:**
```markdown
✅ We're colleagues working together. I need your honest technical judgment.
❌ You should probably tell me if I'm wrong.
```
### 6. Reciprocity
**What it is:** Obligation to return benefits received.
**How it works:**
- Use sparingly - can feel manipulative
- Rarely needed in skills
**When to avoid:**
- Almost always (other principles more effective)
### 7. Liking
**What it is:** Preference for cooperating with those we like.
**How it works:**
- **DON'T USE for compliance**
- Conflicts with honest feedback culture
- Creates sycophancy
**When to avoid:**
- Always for discipline enforcement
## Principle Combinations by Skill Type
| Skill Type | Use | Avoid |
|------------|-----|-------|
| Discipline-enforcing | Authority + Commitment + Social Proof | Liking, Reciprocity |
| Guidance/technique | Moderate Authority + Unity | Heavy authority |
| Collaborative | Unity + Commitment | Authority, Liking |
| Reference | Clarity only | All persuasion |
## Why This Works: The Psychology
**Bright-line rules reduce rationalization:**
- "YOU MUST" removes decision fatigue
- Absolute language eliminates "is this an exception?" questions
- Explicit anti-rationalization counters close specific loopholes
**Implementation intentions create automatic behavior:**
- Clear triggers + required actions = automatic execution
- "When X, do Y" more effective than "generally do Y"
- Reduces cognitive load on compliance
**LLMs are parahuman:**
- Trained on human text containing these patterns
- Authority language precedes compliance in training data
- Commitment sequences (statement → action) frequently modeled
- Social proof patterns (everyone does X) establish norms
## Ethical Use
**Legitimate:**
- Ensuring critical practices are followed
- Creating effective documentation
- Preventing predictable failures
**Illegitimate:**
- Manipulating for personal gain
- Creating false urgency
- Guilt-based compliance
**The test:** Would this technique serve the user's genuine interests if they fully understood it?
## Research Citations
**Cialdini, R. B. (2021).** *Influence: The Psychology of Persuasion (New and Expanded).* Harper Business.
- Seven principles of persuasion
- Empirical foundation for influence research
**Meincke, L., Shapiro, D., Duckworth, A. L., Mollick, E., Mollick, L., & Cialdini, R. (2025).** Call Me A Jerk: Persuading AI to Comply with Objectionable Requests. University of Pennsylvania.
- Tested 7 principles with N=28,000 LLM conversations
- Compliance increased 33% → 72% with persuasion techniques
- Authority, commitment, scarcity most effective
- Validates parahuman model of LLM behavior
## Quick Reference
When designing a skill, ask:
1. **What type is it?** (Discipline vs. guidance vs. reference)
2. **What behavior am I trying to change?**
3. **Which principle(s) apply?** (Usually authority + commitment for discipline)
4. **Am I combining too many?** (Don't use all seven)
5. **Is this ethical?** (Serves user's genuine interests?)