Pattern Analysis

Identify signals → classify patterns → validate with evidence → document for reuse.

<when_to_use>

• Recognizing recurring themes in work or data
• Codifying best practices from experience
• Extracting workflows from repeated success
• Identifying anti-patterns from repeated failures
• Building decision frameworks from observations

NOT for: single occurrences, unvalidated hunches, premature abstraction </when_to_use>

<signal_identification>

Success Signals

Look for:

• Completion markers — task finished smoothly, no backtracking
• Positive feedback — confirmation of value or effectiveness
• Repetition — same approach used 3+ times across different contexts
• Efficiency — solved problem faster/cleaner than alternatives

Frustration Signals

Watch for:

• Backtracking — undoing previous work, starting over
• Clarification loops — multiple rounds to understand intent
• Rework — implementing, then replacing with different approach
• Confusion markers — misalignment between expectation and outcome

Workflow Signals

Identify:

• Sequence consistency — same steps in same order
• Decision points — recurring choices at specific moments
• Quality gates — checkpoints before proceeding
• Exit conditions — how completion is determined </signal_identification>

<pattern_classification>

Workflow Pattern

Characteristics:

• Sequential phases with clear transitions
• Decision points triggering next steps
• Quality gates or validation checkpoints
• Repeatable across similar contexts

Orchestration Pattern

Characteristics:

• Coordinates multiple components or actors
• Manages state across sub-tasks
• Routes work based on conditions
• Aggregates results

Heuristic Pattern

Characteristics:

• Decision-making guideline
• Condition → action mapping
• Context-sensitive application
• Often has exceptions

Anti-Pattern

Characteristics:

• Common mistake leading to rework
• Inefficiency despite seeming reasonable
• Causes specific failure modes
• Has better alternative </pattern_classification>

<evidence_thresholds>

Codification Criteria

Don't codify after first occurrence. Require:

• 3+ instances — minimum repetition to establish pattern
• Multiple contexts — works across different scenarios
• Clear boundaries — know when to apply vs not apply
• Measurable benefit — improves outcome compared to ad-hoc approach

Quality Indicators

Strong patterns show:

• Consistency — same structure each time
• Transferability — others can follow it
• Robustness — handles edge cases gracefully
• Efficiency — saves time/effort

Weak patterns show:

• Variation — changes significantly each use
• Expertise dependency — only works for specific person
• Fragility — breaks on slight deviation
• Overhead — costs more than value provided </evidence_thresholds>

<quality_criteria_extraction>

From Success Cases

Analyze what made successful outcomes work:

1. Identify outcome — what was delivered?
2. Trace approach — what steps led there?
3. Extract principles — what rules were followed?
4. Generalize — how does this apply elsewhere?

From Failure Cases

Learn from unsuccessful attempts:

1. Identify failure — what went wrong?
2. Trace cause — which decision caused it?
3. Extract constraint — what rule was violated?
4. Prevent — how to catch this earlier?

Comparative Analysis

When multiple approaches exist:

1. Enumerate options — list all approaches tried
2. Compare outcomes — which worked better?
3. Isolate variables — what was different?
4. Extract criteria — when to use each? </quality_criteria_extraction>

<pattern_documentation>

Minimum Viable Pattern

Capture:

• Name — memorable, descriptive
• When — trigger conditions
• What — core workflow or rule
• Why — problem it solves

Full Pattern

Add:

• How — detailed steps
• Examples — concrete cases
• Variations — adaptations for different contexts
• Anti-patterns — common mistakes
• References — supporting material </pattern_documentation>

<progressive_formalization> Observation (1–2 instances):

• Note for future reference
• "This worked well, watch for recurrence"

Hypothesis (3+ instances):

• Draft informal guideline
• Test consciously in next case
• Gather feedback

Codification (validated pattern):

• Create formal documentation
• Include examples and constraints
• Make discoverable

Refinement (ongoing):

• Update based on usage
• Add edge cases
• Improve clarity </progressive_formalization>

<workflow> Loop: Observe → Classify → Validate → Document

1. Collect signals — note successes, failures, recurring behaviors
2. Classify pattern type — workflow, orchestration, heuristic, anti-pattern
3. Check evidence threshold — 3+ instances? Multiple contexts?
4. Extract quality criteria — what makes it work?
5. Document pattern — name, when, what, why
6. Test deliberately — apply consciously, track variance
7. Refine — adjust based on feedback </workflow>

<rules> ALWAYS: - Require 3+ instances before codifying - Validate across multiple contexts - Document both when to use AND when not to - Include concrete examples - Track pattern effectiveness over time

NEVER:

• Codify after single occurrence
• Abstract without evidence
• Ignore context-sensitivity
• Skip validation step
• Assume transferability without testing </rules>

<references> Related skills: - [patternify](../patternify/SKILL.md) — pattern discovery from conversations - [codebase-analysis](../codebase-analysis/SKILL.md) — uses pattern analysis for code investigation - [report-findings](../report-findings/SKILL.md) — presenting discovered patterns </references>