deep-recon-teams

Experimental fork of deep-recon that uses Claude Code's agent teams instead of subagents.

Four specialized agents run in parallel rounds — but now they can talk to each other mid-round. The hypothesis: inter-agent dialogue (Critic challenging Explorer directly, Synthesizer requesting clarification) produces sharper output than brokering everything through the orchestrator.

Architecture

deep-recon (subagents) — hub-and-spoke

         ┌──────────┐
         │   Lead    │
         └────┬─────┘
        ┌─────┼─────┐
        ▼     ▼     ▼     ▼
     Explore  Assoc  Crit  Synth
        │     │     │     │
        └─────┼─────┘     │
              ▼            │
         Lead collects ────┘
         Lead redistributes
              ▼
         Next round

Agents report to the Lead. The Lead digests, cross-pollinates, dispatches the next round. Critic→Explorer challenges take a full round delay.

deep-recon-teams (agent teams) — mesh within rounds

         ┌──────────┐
         │   Lead    │
         └────┬─────┘
              │ (round transitions only)
        ┌─────┼─────┐
        ▼     ▼     ▼     ▼
     Explore ↔ Assoc ↔ Crit → Synth
        │     │     │        │
        └─────┼─────┘        │
              │               │
         Lead reads files ────┘
         Lead cross-pollinates
              ▼
         Next round

Agents message each other within rounds. The Critic challenges the Explorer and Associator during the round. The Explorer's report already incorporates the challenge. The Synthesizer gets pre-sharpened material.

The Lead still controls round transitions and cross-pollination — the interpretive step between rounds stays deterministic.

Round structure

Round 1:

• Explorer, Associator, Critic start simultaneously
• Mid-round messaging: Critic challenges, Explorer/Associator handoffs
• Synthesizer is gated — waits until the other three finish, then reads their reports
• Lead cross-pollinates after Synthesizer completes

Round 2+:

• All four agents start simultaneously (Synthesizer runs in parallel)
• Mid-round messaging continues
• Lead cross-pollinates after the round

Round 3: Created dynamically if the Synthesizer recommends it (autonomous) or the user requests it (interactive).

Inter-agent messaging patterns

Sender	Recipient	Pattern
Critic	Explorer	"You found X. Does it hold when Y?"
Critic	Associator	"X↔Y analogy breaks at Z. Better parallel?"
Explorer	Associator	"Found source on X, might connect to vault note [[Y]]"
Associator	Explorer	"Can you search for X? My connection depends on it"
Synthesizer	Any	"Your finding X contradicts Z. Clarify?"

Messages are brief (2-3 sentences), actionable. No agent messages the Lead mid-round.

The Agents

Agent	Style	Role
Explorer	Divergent	Casts the widest net — web searches, vault searches, adjacent fields, historical parallels
Associator	Lateral	Finds non-obvious connections — structural analogies, cross-domain pattern matching, productive metaphors
Critic	Adversarial	Stress-tests emerging ideas — prior art, hidden assumptions, steelmanned objections, productive contradictions
Synthesizer	Integrative	Identifies emergent patterns across all inputs — distinct framings, tensions worth preserving, the question the user hadn't considered

Modes

Flag	Mode	Description
(default)	Interactive	Socratic — checks in between rounds for user steering
--autonomous	Autonomous	Runs all rounds, delivers finished document
(default)	Explore	Divergent — opens possibility space, ends with open questions
--focus	Focus	Convergent — narrows to one argument, ends with action plan
--vault-only	Vault-only	Skips web search, uses only vault content
--pdfs	PDF collection	Explorer downloads relevant PDFs to <output_dir>/PDFs/

Prerequisites

• Claude Code with agent teams support
• CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 in environment or settings.json
• An Obsidian vault
• Web search access (unless using --vault-only)

The skill fails fast if agent teams aren't available. No graceful degradation — use /deep-recon instead.

Installation

Copy the deep-recon-teams directory into your .claude/skills/ directory:

your-project/
└── .claude/
    └── skills/
        └── deep-recon-teams/
            ├── SKILL.md
            ├── agents/
            │   ├── explorer.md
            │   ├── associator.md
            │   ├── critic.md
            │   └── synthesizer.md
            └── templates/
                └── brainstorm-output.md

Then add the skill to your CLAUDE.md:

### /deep-recon-teams - Deep Reconnaissance (Agent Teams)
Experimental fork of deep-recon using agent teams for inter-agent dialogue.
Requires CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1. Use /deep-recon for stable version.

Usage

/deep-recon-teams <topic or question>

Examples:

/deep-recon-teams the relationship between infrastructure decay and political legitimacy
/deep-recon-teams --autonomous --focus what makes network culture different from digital culture
/deep-recon-teams --vault-only connections between my notes on sound art and landscape

Experimental Caveats

1. Token cost: Expect 3-5x more tokens than subagent deep-recon. Inter-agent messaging adds overhead. The Synthesizer gating in R1 adds a sequential step.
2. No session resumption: If the session breaks mid-run, output files on disk are the recovery path. Individual agent reports in recon/rN-<role>.md survive.
3. Task status lag: The Lead verifies completion via output files on disk, not just task status. If the file exists and has a timing block, the agent finished.
4. Shutdown can be slow: After the final round, the Lead proceeds with formatting while teammates wind down.
5. No per-agent token counts: Agent teams mode doesn't expose Task metadata. The Process Log reports wall-clock times only.
6. Untested at scale: This is an experiment to compare output quality between subagent and agent-teams architectures. Report issues to help evaluate the approach.

Metrics

Per-agent token counts are unavailable in agent teams mode. The Process Log reports:

• Per-agent wall-clock times (from timestamps each agent writes)
• Per-round wall-clock times
• Cumulative wall-clock time

Compare with subagent deep-recon's token metrics to evaluate cost/quality tradeoff.

Output

Same structure as deep-recon:

• Central Question — the refined driving question
• The Territory — 3-5 fully developed framings
• Tensions — productive frictions between framings
• Unexpected Connections — cross-domain links as prose
• Open Questions — genuinely open, not rhetorical
• Sources — vault wikilinks and web references
• Process Log — mode, intention, round count, wall-clock times

Individual agent reports are saved alongside as reference material.

vs. deep-recon

	deep-recon	deep-recon-teams
Architecture	Subagents (Task tool)	Agent teams (experimental)
Inter-agent comms	None (Lead brokers)	Direct mid-round messaging
Critic→Explorer delay	1 round	Same round
Synthesizer R1	Parallel with others	Gated (waits for others)
Token tracking	Per-agent counts	Wall-clock only
Token cost	Baseline	~3-5x more
Stability	Production	Experimental
Env requirement	None	CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1

License

MIT