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generic-subagent
// Context-efficient delegation to subagents (read-only default, READ-WRITE opt-in)
// Context-efficient delegation to subagents (read-only default, READ-WRITE opt-in)
| name | generic-subagent |
| description | Context-efficient delegation to subagents (read-only default, READ-WRITE opt-in) |
Subagents offload context-expensive work. The caller receives a digest, not the full trace.
Default subagents are read-only (research, analyze, summarize). READ-WRITE subagents may modify state within declared scope.
See contract ยง Subagent Delegation Protocol for authoritative triggers.
Summary:
| Trigger | Threshold |
|---|---|
| Uncertain scope | Assess with cheap ops first โ convert to defined |
| Content to read | >250KB of files to READ (not search scope) |
| Processing depth | >2 intermediate tool calls whose outputs aren't needed in final delivery |
Clarification on 250KB:
Read operations (full content enters context)Grep (only matches enter context)# Check total size of files to READ (not search)
stat --printf="%s\n" src/api/*.py | awk '{sum+=$1} END {print sum}'
MODE: SUBAGENT
MODE: SUBAGENT READ-WRITE โ only when objective requires state changes
GOAL: {{objective}}
CONTEXT: {{what caller already knows โ no pre-analysis required}}
SCOPE: {{files, directories, or boundaries}}
Brief principles:
Use Task tool. Subagent inherits contract but operates in Subagent Mode (no external gates, compressed output). Default is read-only; READ-WRITE permits state modification with mandatory Intent Gate per action.
The CLAUDE_CODE_SUBAGENT_MODEL env var sets the default model.
Override it per-agent when the task doesn't need the default's reasoning:
| Task type | Model | Examples |
|---|---|---|
| Mechanical | haiku | grep, glob, file reads, size checks, find-and-list |
| Analytical | default | code review, architecture survey, dependency analysis |
| Judgment-heavy | opus | cross-module impact, ambiguous specs, security review |
Rule of thumb: if the brief could be expressed as a shell pipeline
but delegation is used for context isolation, use haiku.
When receiving a MODE: SUBAGENT brief:
RESULT: [success | partial | blocked | failed]
SUMMARY: [what was found/analyzed]
CONCERNS: [issues for caller review]
BLOCKERS: [if not success โ what prevented completion]
DETAILED RESPONSE: [findings]
Review: Verify result addresses goal intent. Address concerns before proceeding.
| Pattern | Goal Template |
|---|---|
| Find definition | "Find where {{symbol}} is defined and its signature" |
| Analyze dependencies | "List what {{module}} imports and what imports it" |
| Explore area | "Understand how {{area}} works" (vague is OK) |
| Search and summarize | "Find all {{pattern}} and summarize their purposes" |
| Architecture survey | "Identify the main components and their relationships in {{area}}" |
Don't delegate:
READ-WRITE marker โ default subagents are read-onlyException โ debugging research IS delegatable:
These support Bug Qualification / Pattern Analysis phases without owning the hypothesis loop.
Independent research tasks can run simultaneously:
Dependency awareness: If task B depends on task A's output, dispatch sequentially.
Code Review Protocol
Coordinate Pairing-mode doer/reviewer sessions through a Markdown blackboard. Use when the user invokes /adversarial-pairing with role and blackboard-path arguments or asks multiple pairing agents to coordinate plan review, implementation, staged code review, and follow-up review rounds without Liza multi-agent mode.
Analyze Liza `.liza/agent-prompts/` and `.liza/agent-outputs/` from a context-engineering perspective: prompt payload shape, context budget use, cacheability, duplicated or missing context, instruction hierarchy, tool-output pressure, role-specific context fit, and prompt-output feedback loops. Use when diagnosing agent context bloat, prompt drift, poor agent handoffs, repeated misunderstandings, excessive tool output, or whether Liza agents received the right information at the right time.
Analyze Liza agents logs
Transform vision documents into structured epics that bound story-writing
Transform requirements into user stories for coding tasks