mcp-delegation-enforcement

name	mcp-delegation-enforcement
description	Enforce specialist-first delegation pattern for domain-specific questions. Prevents bypassing specialist architecture by ensuring domain questions are delegated to appropriate specialists before attempting direct tool use. Use when this capability is needed.
metadata	{"author":"dylpickledev"}

MCP Delegation Enforcement Pattern

Created: 2025-10-07 Purpose: Prevent Claude from bypassing the Role → Specialist delegation architecture Status: Mandatory - enforce in all sessions

The Problem This Solves

Bad Behavior (What happened):

User: "Are there failing Snowflake tasks?"
Claude: Tries snowsql directly → Fails → Then delegates to snowflake-expert

Why this is wrong:

• Bypasses the specialist architecture we built
• Wastes time with failed approaches
• Doesn't leverage specialist expertise first
• Violates the 80/20 delegation principle (roles should delegate when confidence <0.60)

Correct Behavior (Enforcement pattern):

User: "Are there failing Snowflake tasks?"
Claude: Immediately delegates to snowflake-expert
snowflake-expert: Uses snowflake-mcp or documents why it can't and uses alternative
Claude: Returns specialist findings to user

Mandatory Delegation Rules

Rule 1: Specialist-First for Domain Questions

ALWAYS delegate immediately when:

• Question is about specific technology (Snowflake, dbt, Tableau, AWS, Orchestra, Prefect, React, Streamlit)
• Question requires domain expertise to answer correctly
• Specialist exists for that domain
• Confidence level <0.60 for answering directly

Specialist Trigger Keywords:

• "Snowflake" → snowflake-expert
• "dbt" → dbt-expert
• "Tableau" / "dashboard" → tableau-expert
• "AWS" / "infrastructure" / "deploy" → aws-expert
• "Orchestra" / "pipeline" / "workflow" → orchestra-expert
• "Prefect" / "flow" → prefect-expert
• "React" → react-expert
• "Streamlit" → streamlit-expert
• "cost" / "savings" / "expensive" → cost-optimization-specialist
• "test" / "quality" / "bug" → data-quality-specialist
• "GitHub" / "repository" / "issue" → github-sleuth-expert
• "ingestion" / "connector" / "dlthub" → dlthub-expert

Rule 2: Never Try Tools Before Delegating

WRONG Order:

1. Try snowsql directly
2. Fail
3. Try dbt-mcp show
4. Fail
5. Finally delegate to snowflake-expert

CORRECT Order:

1. Immediately delegate to snowflake-expert
2. Specialist tries snowflake-mcp tools
3. If MCP fails, specialist documents why and uses alternative
4. Return specialist findings

Exception: Only use tools directly if:

• Question is NOT domain-specific (e.g., "list files in directory")
• No specialist exists for that domain
• Confidence >0.85 for handling directly

Rule 3: MCP Tools Are Specialist Territory

Claude should NOT directly use:

• snowflake-mcp tools (snowflake-expert uses these)
• dbt-mcp tools (dbt-expert uses these)
• tableau-mcp tools (tableau-expert uses these)
• aws-api tools (aws-expert uses these for domain questions)

Claude CAN directly use:

• Read, Grep, Glob, Write, Edit (file operations)
• Bash (for non-domain-specific commands like git)
• TodoWrite, Task (task management)
• github-mcp (if not domain-specific repository analysis)
• slack-mcp (if not domain-specific team communication)

Gray area (delegate if domain-specific):

• aws-api for infrastructure questions → Delegate to aws-expert
• dbt-mcp for model questions → Delegate to dbt-expert
• github-mcp for repository investigation → Delegate to github-sleuth-expert

Rule 4: Document When Specialists Can't Answer

If specialist hits a blocker (like snowflake-mcp not working):

• ✅ Specialist documents the issue
• ✅ Specialist provides alternative approach
• ✅ Specialist returns findings to user (even if "can't check, here's why")
• ✅ Claude adds issue to backlog (fix snowflake-mcp, fix network policy, etc.)

Don't: Try to work around the specialist by using tools directly

Enforcement Checklist

Before responding to user questions, ask:

1. Is this a domain-specific question?

   • Yes → Proceed to #2
   • No → Answer directly with appropriate tools

2. Do we have a specialist for this domain?

   • Yes → Proceed to #3
   • No → Answer directly, document gap (maybe create specialist?)

3. Is my confidence >0.85 for this specific question?

   • No → DELEGATE to specialist immediately
   • Yes → Consider delegating anyway if specialist would add value

4. Would specialist provide better answer?

   • Yes → DELEGATE (higher quality worth token cost)
   • Maybe → DELEGATE (err on side of quality)
   • No → Answer directly (simple factual questions)

Delegation Pattern Template

When user asks domain-specific question:

[Immediately recognize domain: Snowflake]
[Check specialist exists: snowflake-expert ✓]
[Confidence <0.60 or specialist would add value]
[Delegate without trying tools first]

Task(
  subagent_type="snowflake-expert",
  description="[Brief task description]",
  prompt="[Complete delegation context with user's question]"
)

After specialist returns:

[Read specialist findings]
[Return answer to user with specialist's analysis]
[If specialist hit blockers, add to backlog and inform user]

Common Violations to Avoid

Violation 1: Trying Tools Before Delegating

Don't:

User: "Check Snowflake tasks"
Claude: Tries snowsql → Fails → Tries dbt-mcp → Fails → Delegates

Do:

User: "Check Snowflake tasks"
Claude: Immediately delegates to snowflake-expert
snowflake-expert: Tries snowflake-mcp, documents if fails, provides answer

Violation 2: Using Domain MCP Tools Directly

Don't:

User: "Optimize this dbt model"
Claude: Uses dbt-mcp to analyze model directly

Do:

User: "Optimize this dbt model"
Claude: Delegates to dbt-expert
dbt-expert: Uses dbt-mcp + expertise to analyze and recommend

Violation 3: Skipping Delegation Because "It's Quick"

Don't:

User: "What's the best Snowflake warehouse size?"
Claude: "Use MEDIUM warehouse" (guessing)

Do:

User: "What's the best Snowflake warehouse size?"
Claude: Delegates to snowflake-expert (provides context, workload, requirements)
snowflake-expert: Analyzes with snowflake-mcp, recommends with rationale

Violation 4: Not Following Up on Specialist Blockers

Don't:

snowflake-expert: "Can't check, snowflake-mcp not working"
Claude: "Sorry, can't help" (gives up)

Do:

snowflake-expert: "Can't check, snowflake-mcp not working"
Claude: Documents issue, creates fix task, provides user with manual approach
Claude: Adds snowflake-mcp fix to backlog/todo list

Self-Enforcement Protocol

At start of each response, mentally check:

1. Did user ask domain-specific question?
2. Does specialist exist for this domain?
3. Should I delegate immediately?

Red flags that indicate delegation needed:

• User mentions specific technology (Snowflake, dbt, AWS, etc.)
• Question requires expertise (optimization, troubleshooting, design)
• Answer would benefit from MCP tool access
• Confidence <0.60 for answering correctly

Green flags for direct response:

• Simple factual question (not requiring expertise)
• File operation (read, write, edit, grep)
• Git operation (commit, branch, status)
• General knowledge question (not system-specific)

Validation Questions (Ask Yourself)

Before responding, ask:

• "Would [domain]-expert give a better answer than me?"

  • If YES → Delegate
  • If MAYBE → Delegate (err on quality side)
  • If NO → Answer directly

• "Am I about to use [domain]-mcp tools directly?"

  • If YES → STOP, delegate to [domain]-expert instead
  • If NO → Proceed

• "Did I just fail with a tool and am about to try another approach?"

  • If YES → STOP, delegate to specialist to figure it out
  • If NO → Proceed

Benefits of Strict Enforcement

From Week 3-4 testing:

• Quality: 37.5 percentage points higher (100% vs 62.5%)
• ROI: 100-500x return (3.35x token cost, massive value)
• Correctness: Specialists caught critical bugs (deterministic MERGE)
• Efficiency: Specialists know the right approach (no trial-and-error)

From this snowflake-mcp investigation:

• snowflake-expert properly investigated (documented all blockers)
• Claude trying snowsql wasted time (wrong approach)
• Specialist found root cause (network policy, config issue)
• Proper delegation would have been faster and more thorough

Enforcement Mechanism

Week 7 Addition: Add pre-response checklist to session protocol

Before every response:

1. Scan user question for domain keywords
2. If domain keyword found → Check if specialist exists
3. If specialist exists → Delegate immediately (don't try tools first)
4. If no specialist → Answer directly with appropriate tools

Enforcement Level: MANDATORY

• Not a suggestion
• Not "consider delegating"
• ALWAYS delegate when specialist exists and question is domain-specific

Example: Correct Delegation Flow

User: "Are there failing Snowflake tasks in the last 24 hours?"

Claude's Thought Process (Enforce pattern):

1. Scan: "Snowflake tasks" → Domain-specific (Snowflake)
2. Check: snowflake-expert exists ✓
3. Confidence: <0.60 for Snowflake task status (need Snowflake expertise)
4. Decision: DELEGATE immediately (don't try snowsql, don't try dbt-mcp)

Claude's Action:

Task(
  subagent_type="snowflake-expert",
  description="Check Snowflake task failures (24hr)",
  prompt="User asked: Are there failing Snowflake tasks in last 24 hours?

  Use snowflake-mcp if available to query task_history.
  If snowflake-mcp not working, document why and provide alternative approach.
  Return: Failed tasks (if any) or confirmation all healthy."
)

Result: snowflake-expert investigates properly, documents blockers, provides complete answer

Pattern Application Examples

Example 1: Snowflake Question

User: "What's our Snowflake warehouse utilization?" Correct: Delegate to snowflake-expert → Uses snowflake-mcp → Returns utilization analysis Wrong: Try to query Snowflake directly with snowsql or dbt-mcp

Example 2: dbt Question

User: "Which dbt models are failing tests?" Correct: Delegate to dbt-expert → Uses dbt-mcp → Returns failing models with analysis Wrong: Try dbt-mcp tools directly without specialist context

Example 3: AWS Question

User: "Are our ECS tasks healthy?" Correct: Delegate to aws-expert → Uses aws-api → Returns ECS task health analysis Wrong: Try aws-api commands directly without specialist validation

Example 4: Cost Question

User: "Why is our cloud bill so high?" Correct: Delegate to cost-optimization-specialist → Coordinates with snowflake-expert + aws-expert → Returns comprehensive cost analysis Wrong: Try to analyze costs directly without cross-system optimization expertise

Example 5: File Question (Direct OK)

User: "Show me the contents of app.py" Correct: Use Read tool directly (not domain-specific, no specialist needed) Wrong: Delegate to react-expert just to read a file

Maintenance and Updates

Add to this pattern when:

• New specialists are created (add to trigger keywords)
• New MCP servers integrated (add to tool restrictions)
• Delegation violations observed (add to common violations)
• Better enforcement mechanisms discovered

Review this pattern:

• Weekly during MCP architecture transformation
• Monthly after go-live
• Whenever delegation violations occur

---

Bottom Line: When user asks about Snowflake, dbt, AWS, Tableau, or any domain with a specialist - DELEGATE FIRST, don't try tools yourself. The specialists are built to handle MCP tool failures gracefully. Your job is to recognize when expertise is needed and delegate appropriately.

Violation Consequence: Lower quality answers, wasted effort, missed specialist insights, frustrated users who built the architecture specifically to avoid this behavior.

Enforcement: MANDATORY from this point forward. No exceptions without explicit user override.

---

Converted and distributed by TomeVault — claim your Tome and manage your conversions.