athola/delegation-core

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

1. Task Assessment: Classify task by complexity and context size.
2. Suitability Evaluation: Check prerequisites and service fit.
3. Handoff Planning: Formulate request and document plan.
4. 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.md for 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.md for 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.md for 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.