Conversation Analysis

Signal extraction → pattern detection → behavioral insights.

<when_to_use>

• User requests conversation analysis

• Identifying frustration, success, or workflow patterns

• Extracting user preferences and requirements

• Understanding task evolution and iterations

NOT for: real-time monitoring, content generation, single message analysis

</when_to_use>

<signal_taxonomy>

Type Subtype Indicators

Success Explicit Praise "Perfect!", "Exactly what I needed", exclamation marks

Success Continuation "Now do the same for...", building on prior work

Success Adoption User implements suggestion without modification

Success Acceptance "Looks good", "Ship it", "Merge this"

Frustration Correction "No, I meant...", "That's wrong", "Do X instead"

Frustration Reversion User undoes agent changes, "Go back"

Frustration Repetition Same request 2+ times, escalating specificity

Frustration Explicit "This isn't working", "Why did you...", accusatory tone

Workflow Sequence "First...", "Then...", "Finally...", numbered lists

Workflow Transition "Now that X is done, let's Y", phase changes

Workflow Tool Chain Recurring tool usage patterns (Read → Edit → Bash)

Workflow Context Switch Abrupt topic changes, no transition language

Request Prohibition "Don't use X", "Never do Y", "Avoid Z"

Request Requirement "Always check...", "Make sure to...", "You must..."

Request Preference "I prefer...", "It's better to...", comparative language

Request Conditional "If X then Y", "When A, do B", situational rules

Confidence levels:

• High (0.8–1.0): Explicit keywords match taxonomy, no ambiguity, strong context

• Medium (0.5–0.79): Implicit signal, partial context, minor ambiguity

• Low (0.2–0.49): Ambiguous language, weak context, borderline classification

</signal_taxonomy>

Track with TodoWrite. Phases advance only, never regress.

Phase Trigger activeForm

Parse Input Session start "Parsing input"

Extract Signals Scope validated "Extracting signals"

Detect Patterns Signals extracted "Detecting patterns"

Synthesize Report Patterns detected "Synthesizing report"

TodoWrite format:

• Parse Input { scope description }
• Extract Signals { from N messages }
• Detect Patterns { category focus }
• Synthesize Report { output format }

Edge cases:

• Small scope (<5 messages): Skip Extract Signals, jump to Synthesize

• Re-analysis: Resume at Detect Patterns

• Narrow focus (single signal type): Skip Detect Patterns

Workflow:

• Start: Create Parse Input in_progress

• Transition: Mark current completed , add next in_progress

• After delivery: Mark Synthesize Report completed

Define Scope

• Message range (all, recent N, date range)

• Actors (user only, agent only, both)

• Exclusions (system messages, tool outputs, code blocks)

• Mark Parse Input completed , create Extract Signals in_progress

Extract Signals

• Scan messages for signal keywords

• Match against taxonomy

• Assign confidence (high/medium/low)

• Record: type, subtype, message_id, timestamp, quote, context

• Mark Extract Signals completed , create Detect Patterns in_progress

Detect Patterns

• Group signals by type/subtype

• Find clusters (3+ related signals)

• Identify evolution (signal changes over time)

• Track repetition (recurring themes)

• Spot correlations (tool chains, workflows)

• Mark Detect Patterns completed , create Synthesize Report in_progress

Output

• Generate JSON with signals, patterns, summary

• Include confidence, recommendations, action items

• Append △ Caveats if gaps exist

• Mark Synthesize Report completed

<pattern_detection>

Behavioral patterns from signal clusters:

Pattern Detection Confidence

Repetition Same signal 3+ times Strong: 5+ signals

Evolution Signal type changes over time Moderate: 3-4 signals

Preferences Consistent request signals Strong: across sessions

Tool Chains Recurring tool sequences (5+ times) High: frequent use

Problem Areas Clustered frustration signals Strong: 3+ in same topic

Temporal patterns:

• Escalation: Increasing frustration/stronger requirements

• De-escalation: Frustration → success transition

• Cyclical: Same issue recurs across sessions

</pattern_detection>

<output_format>

JSON structure:

{ "analysis": { "scope": { "message_count": N, "date_range": "YYYY-MM-DD to YYYY-MM-DD", "actors": ["user", "agent"] }, "signals": [ { "type": "success|frustration|workflow|request", "subtype": "specific_subtype", "message_id": "msg_123", "timestamp": "ISO8601", "quote": "exact text", "confidence": "high|medium|low", "context": "brief explanation" } ], "patterns": [ { "pattern_type": "repetition|evolution|preference|tool_chain", "category": "success|frustration|workflow|request", "description": "pattern summary", "occurrences": N, "confidence": "strong|moderate|weak", "first_seen": "ISO8601", "last_seen": "ISO8601", "recommendation": "actionable next step" } ], "summary": { "total_signals": N, "by_type": { "success": N, "frustration": N, ... }, "key_insights": ["insight 1", "insight 2"], "action_items": ["item 1", "item 2"] } } }

</output_format>

ALWAYS:

• Create Parse Input at session start

• Update todos at phase transitions

• Include confidence levels for all signals

• Support patterns with 2+ signals minimum

• Mark Synthesize Report completed after delivery

• Apply recency weighting (recent overrides old)

NEVER:

• Skip phase transitions

• Extract low-confidence signals without marking them

• Claim patterns from single occurrences

• Regress phases

• Deliver without marking final phase complete

• Over-interpret neutral language

• signal-patterns.md — extended taxonomy, edge cases

• extraction-techniques.md — regex, heuristics

• sample-analysis.md — complete walkthrough