Table of Contents
- Overview
- When to Use
- Philosophy
- Delegation Flow
- Quick Decision Matrix
- Detailed Workflow Steps
- 1. Task Assessment (
delegation-core:task-assessed) - 2. Suitability Evaluation (
delegation-core:delegation-suitability) - 3. Handoff Planning (
delegation-core:handoff-planned) - 4. Execution & Integration (
delegation-core:results-integrated) - Leyline Infrastructure
- Service-Specific Skills
- Module Reference
- Exit Criteria
Delegation Core Framework
Overview
A method for deciding when and how to delegate tasks to external LLM services. Core principle: delegate execution, retain high-level reasoning.
When To Use
- Before invoking external LLMs for task assistance.
- When operations are token-heavy and exceed local context limits.
- When batch processing benefits from different model characteristics.
- When tasks require routing between models.
When NOT To Use
- Task requires reasoning by Claude
Philosophy
Delegate execution, retain reasoning. Claude handles architecture, strategy, design, and review. External LLMs perform data processing, pattern extraction, bulk operations, and summarization.
Delegation Flow
- Task Assessment: Classify task by complexity and context size.
- Suitability Evaluation: Check prerequisites and service fit.
- Handoff Planning: Formulate request and document plan.
- Execution & Integration: Run delegation, validate, and integrate results.
Quick Decision Matrix
| Complexity | Context | Recommendation | |------------|---------|----------------| | High | Any | Keep local | | Low | Large | Delegate | | Low | Small | Either |
High Complexity: Architecture, design decisions, trade-offs, creative problem solving.
Low Complexity: Pattern counting, bulk extraction, boilerplate generation, summarization.
Detailed Workflow Steps
1. Task Assessment (delegation-core:task-assessed)
Classify the task:
- See
modules/task-assessment.mdfor classification criteria. - Use token estimates to determine thresholds.
- Apply the decision matrix.
Exit Criteria: Task classified with complexity level, context size, and delegation recommendation.
2. Suitability Evaluation (delegation-core:delegation-suitability)
Verify prerequisites:
- See
modules/handoff-patterns.mdfor checklist. - Evaluate cost-benefit ratio using
modules/cost-estimation.md. - Check for red flags (security, real-time iteration).
Exit Criteria: Service authenticated, quotas verified, cost justified.
3. Handoff Planning (delegation-core:handoff-planned)
Create a delegation plan:
- See
modules/handoff-patterns.mdfor request template. - Document service, command, input context, expected output.
- Define validation method.
Exit Criteria: Delegation plan documented.
4. Execution & Integration (delegation-core:results-integrated)
Execute and validate results:
- Run delegation and capture output.
- Validate format and correctness.
- Integrate only after validation passes.
- Log usage.
Exit Criteria: Results validated and integrated, usage logged.
MCP Authentication
OAuth Client Credentials (Claude Code 2.1.30+)
For MCP servers that don't support Dynamic Client Registration (e.g., Slack), pre-configured OAuth client credentials can be provided:
claude mcp add <server-name> --client-id <id> --client-secret <secret>
This enables delegation workflows through MCP servers that require pre-configured OAuth, expanding the range of external services available for task delegation.
Claude.ai MCP Connectors (Claude Code 2.1.46+)
As an alternative to manual OAuth setup, users can configure MCP servers directly in claude.ai at claude.ai/settings/connectors. These connectors are automatically available in Claude Code when logged in with a claude.ai account — no claude mcp add or credential management required. This provides a browser-based auth flow that may be simpler for services with complex OAuth requirements.
Worktree Isolation for File-Modifying Delegations (Claude Code 2.1.49+)
When delegating tasks that modify files to subagents, use isolation: worktree in the agent frontmatter to run each agent in a temporary git worktree. This prevents file conflicts when multiple delegated agents operate in parallel on overlapping paths. The worktree is auto-cleaned if no changes are made; preserved with commits if the agent produces changes.
# Agent frontmatter for isolated delegation
isolation: worktree
Leyline Infrastructure
Conjure uses leyline infrastructure:
| Leyline Skill | Used For |
|---------------|----------|
| quota-management | Track service quotas and thresholds. |
| usage-logging | Session-aware audit trails. |
| service-registry | Unified service configuration. |
| error-patterns | Consistent error handling. |
| authentication-patterns | Auth verification. |
See modules/cost-estimation.md for leyline integration examples.
Service-Specific Skills
For detailed service workflows:
Skill(conjure:gemini-delegation): Gemini CLI specifics.Skill(conjure:qwen-delegation): Qwen MCP specifics.
Execution Modes
When delegating to multiple agents, choose the appropriate execution mode:
| Mode | When to Use | How It Works | |------|-------------|--------------| | single-session | Sequential tasks, same-file edits | Claude works through tasks in order | | subagents | Parallel independent tasks | Agents work independently, report back | | agent-team | Parallel coordinated tasks | Agents can communicate with each other |
See references/execution-modes.md for the selection decision
matrix, mode compatibility notes, and anti-patterns to avoid.
Module Reference
- task-assessment.md: Complexity classification, decision matrix.
- cost-estimation.md: Pricing, budgets, cost tracking.
- handoff-patterns.md: Request templates, workflows.
- troubleshooting.md: Common problems, service failures.
Exit Criteria
- [ ] Task assessed and classified.
- [ ] Delegation decision justified.
- [ ] Results validated before integration.
- [ ] Lessons captured.