/pattern-detect

name: pattern-detect
description: >
  Detect recurring patterns using the Agent Monitor's workflow intelligence —
  toolFlow transitions (tool A → B frequency matrices), recurring workflow
  patterns, agent co-occurrence pairs, model delegation habits, error
  propagation paths by agent depth, and compaction triggers. Use to discover
  habitual usage patterns and anti-patterns.

Pattern Detect

Identify recurring patterns using the Agent Monitor's workflow intelligence engine.

Input

The user provides: **$ARGUMENTS**

Options: "all", "tools", "errors", "workflows", "last N sessions".

Data Sources

| Endpoint | Returns | |----------|---------| | `GET /api/sessions?limit=200` | Session list with status, model, cwd, metadata | | `GET /api/analytics` | tool_usage top 20, event_types, agent_types | | `GET /api/workflows/{sessionId}` | 11 datasets per session (see below) |

Workflow datasets used for pattern detection

| Dataset | Pattern insight | |---------|----------------| | `toolFlow` | **Tool transition matrix**: tool A → tool B with counts — reveals sequential habits | | `patterns` | **Detected workflow patterns**: recurring sequences with frequency scores | | `cooccurrence` | **Agent co-occurrence**: which agents frequently run together | | `modelDelegation` | **Model habits**: which models are chosen for which task types | | `errorPropagation` | **Error patterns**: where errors start and how they cascade by agent depth | | `effectiveness` | **Subagent patterns**: which types succeed most, avg duration per type | | `compaction` | **Compaction triggers**: what causes context overflow | | `complexity` | **Complexity patterns**: session complexity scores over time |

Pattern Categories

1. Tool Chain Patterns (from `toolFlow`)

• **Most common sequences**: Top 10 tool transitions (e.g., Read → Edit: 145 times)
• **Starter tools**: First tool used in sessions (indicates task type)
• **Finisher tools**: Last tool before Stop event
• **Anti-patterns**: Tool → same Tool repeated (retries/failures)
• **Co-occurrence**: Tools that always appear together in sessions

2. Workflow Patterns (from `patterns`)

• **Named patterns**: Workflow sequences the API has detected with frequency
• **Session archetypes**: Common session shapes (short edit, long debug, subagent-heavy)
• **Project-specific**: Patterns that appear in specific working directories

3. Error Patterns (from `errorPropagation` + `event_types`)

• **Error origins**: Which agent depth level produces most errors
• **Cascade patterns**: Errors that trigger chains of follow-up errors
• **APIError frequency**: quota hits, rate_limit, overloaded — by time of day
• **Recovery patterns**: How errors are typically resolved (tool retry vs agent switch)

4. Agent Patterns (from `cooccurrence` + `effectiveness`)

• **Agent pairs**: Which agents are spawned together frequently
• **Delegation patterns**: Main agent → subagent task delegation habits
• **Success by type**: Which subagent types (task/explore/code-review) work best for which tasks

5. Temporal Patterns (from session timestamps + `daily_sessions`)

• **Peak hours**: When sessions cluster
• **Duration patterns**: Short vs long session distribution
• **Day-of-week trends**: Productive days vs quiet days

Output

**Pattern Report** with top 10 patterns ranked by frequency × impact:

• Pattern name and description
• Frequency (occurrences across analyzed sessions)
• Impact: positive (reinforce), negative (eliminate), or neutral (observe)
• Actionable recommendation for each