Vodou Deep Thinking - Persistent Intelligence Analysis

⚠️ HARD RULE — NO BATCH DISPATCH ⚠️

DO NOT plan all add_thought calls upfront and submit them as a parallel tool-use batch. That breaks this skill. The MCP server will reject every call after the first as a duplicate, and the user will see a session of garbage.

The correct flow per thought is:

1. Write ONE add_thought Bash call. Submit it. STOP.
2. Read the response — especially the previousThoughts array and any suggestions.
3. Write the NEXT thought informed by what you just read. Submit it. STOP.
4. Repeat.

Each thought must be a single, completed tool call whose response you actually consume before composing the next thought. If you queue thoughts 1–15 in one tool_use block, you have not understood this skill — re-read this section before continuing.

The server enforces this with three guards: thoughts shorter than 30 chars, thoughts matching the "iteration N of M on:" template, and thoughts duplicating prior ones — all rejected with an error you must read.

Overview

This skill runs a genuine deep thinking session using the Vodou-Enhanced-Thinking MCP server. The agent generates real analytical thoughts via sequential Bash calls — NOT template loops. Each thought must be original analysis that builds on the previous one.

Critical rule: The agent writes every thought. The MCP server stores and tracks them. The agent is not a loop runner — it is the thinker. One add_thought per response cycle. Read. Then write the next.

⏸️ STOPPING POINT 1 — Choose Depth

Before thinking, present the user with depth options:

🧠 Deep Thinking Session: [SHORT TOPIC — 5-10 words max, not the full prompt]

How deep should I go?

1. Quick Analysis (5 thoughts) — Key insights, fast
2. Standard Deep Dive (10 thoughts) — Comprehensive
3. Expert Investigation (15 thoughts) — Exhaustive

Wait for the user to pick 1, 2, or 3.

Agent Instructions — Execute After User Picks Depth

Step 1: Start the session

Extract a SHORT topic (5-10 words) from the user's request. Do NOT use the full prompt as the topic. Use a concise description of what you're actually thinking about.

./vodou-core call Vodou-Enhanced-Thinking start_thinking_session '{"topic": "[SHORT TOPIC]", "estimated_steps": [DEPTH]}'

Capture the session_id from the response.

Show the user:

✨ Session started — ID: [session_id]
🎯 Topic: [SHORT TOPIC]
🔢 Depth: [N] thoughts

Step 2: Generate real thoughts — one Bash call per thought

CRITICAL — ONE CALL PER RESPONSE CYCLE: You must write the actual thought content yourself for EVERY thought. Do NOT pass the user's prompt as the thought. Do NOT repeat the same text. Each thought must be original analysis that builds on what came before. Do NOT submit all N add_thought calls in one tool-use batch. The server WILL reject them and the session will fail.

The pattern is:

1. Submit ONE add_thought.
2. The tool returns a response containing previousThoughts and suggestions.
3. READ THE RESPONSE. Notice what's already been written. Notice what the analyzer suggests.
4. Compose the next thought to answer or extend what you just read.
5. Submit that next add_thought as a SEPARATE tool call in your next response.

For each thought N, call:

./vodou-core call Vodou-Enhanced-Thinking add_thought '{"session_id": "[SESSION_ID]", "thought": "[YOUR ACTUAL ANALYTICAL THOUGHT HERE]", "thought_number": N, "total_thoughts": [DEPTH]}'

What to think about at each stage:

• Thought 1 — Core problem definition. What is actually being asked? What are the key variables? What failure modes exist?
• Thought 2 — Current state analysis. What exists today? What works, what doesn't?
• Thought 3 — Root causes or underlying mechanisms. Why does this happen?
• Thought 4 — Alternatives and tradeoffs. What other approaches exist? What are the costs?
• Thought 5 — Non-obvious connections. What does this relate to that isn't obvious?
• Thought 6 — Second-order effects. If you implement this, what happens downstream?
• Thought 7 — Assumptions and blind spots. What are you assuming? Where could you be wrong?
• Thought 8 — Concrete implementation details. How would this actually be built?
• Thought 9 — Edge cases and failure modes. What breaks this?
• Thought 10 — Synthesis so far. What's the clearest picture emerging?
• Thoughts 11-15 — Go deeper on whatever the analysis reveals needs more attention: security, performance, maintainability, user experience, cost, risk.

After every 3-4 thoughts, run a quality check:

./vodou-core call Vodou-Enhanced-Thinking analyze_thinking '{"session_id": "[SESSION_ID]"}'

Use the gaps and suggestions returned to adjust your next thoughts.

Step 3: Complete the session

After all thoughts are done:

./vodou-core call Vodou-Enhanced-Thinking complete_thinking_session '{"session_id": "[SESSION_ID]", "synthesis": "[YOUR COMPREHENSIVE SYNTHESIS — summarize the key findings, the clearest path forward, and any open questions]"}'

⏸️ STOPPING POINT 2 — After Analysis

⚠️ OUTPUT THE SYNTHESIS ITSELF — narration is not a deliverable

An add_thought call STORES a thought; it does not SHOW it. The user reads only your visible reply, so a reply like "Now the synthesis thought (5)." delivers nothing — all the analysis stays invisible in the database. Whatever you wrote into the thoughts, write the conclusions again here, in full, as visible text.

Output EXACTLY this shape — the synthesis paragraph is mandatory and comes FIRST:

🧠 Deep Thinking Complete — [SHORT TOPIC]
[N] thoughts · quality [score]

[THE FULL SYNTHESIS, 1–3 substantial paragraphs of real findings: what this is, the
key insights, the clearest path forward, and any honest caveats. Written out in
full — not a summary of the fact that you thought, but the thinking itself.]

What's next?

1. Go deeper — 5 more thoughts
2. Done
3. Explore a different angle

If user picks 1, continue adding thoughts to the same session_id. If user picks 2, restate the full synthesis clearly (again — in full, not a pointer to it).

Rules for Good Thoughts

DO:

• Build on previous thoughts — reference what you found in thought N-1
• Be specific — name files, functions, systems, real examples
• Disagree with yourself — if a previous assumption looks wrong, say so
• Quantify when possible — "this adds ~50ms latency" beats "this is slower"
• Connect to the user's actual context (their codebase, their platform, their constraints)

DO NOT:

• Narrate instead of delivering. "Now the synthesis thought (5)." / "Let me add thought 3" is not output — the tool call already stored it, and the user sees none of it. Every visible reply must carry the substance, ending with the full synthesis (see STOPPING POINT 2).
• Repeat the user's prompt as a thought
• Write generic filler ("This is an important topic that deserves consideration")
• Run the same thought twice with different wording
• Use template placeholders — write real content

Advanced Options

Resume a previous session

./vodou-core call Vodou-Enhanced-Thinking list_thinking_sessions '{"status": "active", "limit": 5}'
# Then continue with add_thought using the existing session_id

Branch to a different perspective

Add a thought with "branchFromThought": N to explore an alternative angle without losing the main thread.

Revise a thought

If quality analysis reveals a flawed assumption in thought N, add a new thought with "isRevision": true, "revisesThought": N.

What Makes This Different from a Shallow Run

The Vodou-Enhanced-Thinking server stores thoughts and returns them back with each add_thought call. This means:

• You always have the full history when writing the next thought
• Quality scores improve as you build on previous insights
• Sessions persist — they can be resumed in future conversations
• The session_id is the key to everything — capture it and show it to the user

The garbage output ("Deep analysis iteration N of 5 on: [full prompt]") happens when the agent passes the user prompt as the topic AND runs thoughts mechanically without writing content. This skill fixes both problems: short topic, real thoughts written by the agent.