Deep Explore Skill

SkillDev tools

Multi-wave parallel code exploration orchestrator. Use when: large-scale codebase research, understanding complex cross-domain systems, deep investigation needing multiple perspectives simultaneously. Not for: quick lookup (use code-explore), dual confirmation (use code-investigate), code review (use codex-code-review). Output: unified exploration report with completeness scoring.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Deep Explore Skill skill

What this skill tells your AI

The instructions your AI receives, as published by sd0xdev/sd0x-harness in skills/deep-explore/SKILL.md and read by ahel’s review.

Trigger

  • Keywords: deep explore, large-scale research, multi-agent explore, codebase survey, parallel investigation, comprehensive research, deep dive multiple areas

When NOT to Use

ScenarioAlternative
Quick single-area lookup/code-explore
Dual Claude+Codex confirmation/code-investigate
Git history tracking/git-investigate
Code review/codex-review-fast

Workflow Overview

flowchart TD
    A[Phase 0: Intent Analysis] --> B{Files > 25?}
    B -->|No| C[Redirect to /code-explore]
    B -->|Yes| D[Wave 1: Breadth]
    D --> E[Gather + Claim Registry]
    E --> F[Wave 2: Depth]
    F --> G{Completeness Gate}
    G -->|score >= 80 + no critical Qs| H[Report]
    G -->|score < 80 OR critical Qs| I[Wave 3: Cross-cutting]
    I --> H

Phase 0: Intent Analysis

  1. Parse user's research question
  2. Estimate scope: Grep for related keywords → count unique files
  3. Routing guard: if estimated files <= 25, redirect to /code-explore
  4. Plan shards: identify 2-3 non-overlapping exploration areas

Shard Planning Strategy

PriorityMethodWhen
1User-specified areas (--areas)User knows what to split
2Domain-based clusteringAuto-detect service/provider/hooks/rules boundaries
3Directory-based fallbackWhen domain boundaries unclear

Output: ownership matrix (shard → files).

Wave 1: Breadth (Mandatory)

Fan-out 2-3 Explore agents in parallel. Each agent explores one shard.

Agent({
  description: "Wave 1 Shard A: <area description>",
  subagent_type: "Explore",
  run_in_background: true,
  prompt: <agent-prompt template from references/agent-prompt.md>
});

All agents dispatched in a single message (parallel). Wait for all to complete.

Agent Contract (80/20)

AllocationScopeLimit
80%Primary assigned shardUnlimited findings
20%Peripheral vision (security, edge cases, cross-cutting)Max 2 peripheral findings

Peripheral findings must be evidence-backed (file:line) and tagged: cross-cutting | security | reliability | operability.

Inter-Wave: Gather + Plan

After each wave, the orchestrator:

  1. Collect all agent results
  2. Build claim registry (see references/synthesis.md)
  3. Rank open questions by impact × uncertainty
  4. Build context packet for next wave

Context Packet (what to pass forward)

PassDon't Pass
Evidence-backed facts (file:line)Prior wave conclusions as truth
Open Qs ranked by impact × uncertaintyNarrative interpretations
Do-not-repeat ledger (explored files, executed queries)Full raw findings dump
Contradiction listAgent opinions without evidence

Wave 2: Depth (Mandatory)

Focus on top hotspots from Wave 1, ranked by impact × uncertainty × blast_radius.

  • 2-3 agents, each assigned one hotspot for deep dive
  • Context packet from Wave 1 provided (facts + questions, not conclusions)
  • Agents verify Wave 1 hypotheses independently

Completeness Gate

After Wave 2 (and Wave 3 if run), compute completeness score.

2-Signal Completeness Score

score = round(100 × (0.7 × (1 - novelty_rate) + 0.3 × is_zero(critical_open)))

Where:
  novelty_rate = unique_new_findings / max(1, total_valid_findings)
  critical_open = count(questions where impact=high AND uncertainty=high)
  is_zero(x) = 1 if x == 0, else 0

Zero findings → novelty_rate = 0score = 70 (below threshold → continue).

Stop Conditions

ConditionAction
score >= 80 AND critical_open == 0Stop, output report
score >= 80 AND critical_open > 0Wave 3 (if not yet run)
Wave 3 done AND score < 80Stop with Inconclusive + next actions

Hard-Fail Overrides (force continue)

  • Unanswered critical user question
  • High-severity contradiction unresolved
  • Evidence missing for high-impact claim

Precedence (--waves is hard ceiling)

User --wavesHard-fail activeBehavior
--waves 2NoStop after Wave 2
--waves 2YesStop after Wave 2 with Inconclusive
--waves 3NoAdaptive (stop early if score met)
--waves 3YesForce Wave 3

User --waves never exceeded. Hard-fail emits Inconclusive with explanation.

Wave 3: Cross-cutting (Optional)

Triggered only when:

  • Unresolved critical open questions are cross-cutting, OR
  • Findings >70% concentrated in 1 subsystem, OR
  • High-risk domain flags (auth/security/migration)

If no trigger conditions met, skip Wave 3 even if score < 80.

Agents in Wave 3 follow 80/20 contract. If trigger is cross-cutting, one agent may operate as conditional scout with broader mandate.

Agent Dispatch Contract

// Primary: Agent tool with subagent_type=Explore
Agent({
  description: "Wave N Shard X: <description>",
  subagent_type: "Explore",
  run_in_background: true,
  prompt: `<from references/agent-prompt.md>`
});

Fallback (if Explore dispatch fails):

  1. Retry with subagent_type: "general-purpose"
  2. If still fails → degrade to single-agent inline exploration
  3. Mark coverage gap in report

Claim Registry (Synthesis)

See references/synthesis.md for full algorithm.

StepAction
1. Normalize{claim, evidence(file:line), shard, wave, confidence}
2. DedupKey = canonical_file_path + canonical_claim_text (±5 line tolerance)
3. ConsensusSame claim from 2+ shards → [consensus]
4. ConflictContradicting claims → evidence-weight resolution
5. DivergenceUnresolvable → explicit divergence section

Evidence redaction: follow @rules/logging.md — no secrets, file:line refs only.

Arguments

ArgumentDescriptionDefault
<query>Research topic/questionRequired
--agents NAgents per wave (1-3)3
--waves NMax waves (2-3)3 (adaptive)
--areas "a, b, c"Manual shard specificationAuto-detect
--quickRedirect to /code-exploreOff

Output

See references/synthesis.md for report template.

## Deep Exploration Report: <query>

### Completeness
- Score: <N>/100
- Waves executed: <N>
- Agents dispatched: <N>

### Executive Summary
<2-3 sentence answer to user's question>

### Per-Wave Findings
| Wave | Focus | Key Findings | Open Qs |
|------|-------|-------------|---------|

### Claim Registry
| # | Claim | Evidence | Source | Confidence | Consensus |
|---|-------|----------|--------|------------|-----------|

### Coverage Matrix
| Shard | Files Explored | Ownership |
|-------|---------------|-----------|

### Proactive Discoveries (from 20% peripheral)
| # | Finding | Tag | Evidence |
|---|---------|-----|----------|

### Divergence (if any)
| # | Claim A | Claim B | Source Agents | Status |
|---|---------|---------|--------------|--------|

### Residual Risks
- <remaining unknowns and suggested follow-up commands>

Verification Checklist

  • Phase 0 correctly estimated scope and planned shards
  • Wave 1 dispatched agents in parallel (single message)
  • Wave 2 focused on highest-impact hotspots
  • Completeness score computed and displayed
  • Claim registry built with dedup and conflict resolution
  • Inter-wave context did not pass conclusions as truth
  • Report includes coverage matrix and residual risks
  • No git add/commit/push executed

References

  • Agent prompt template: references/agent-prompt.md
  • Synthesis algorithm + report template: references/synthesis.md
  • Standards: @rules/docs-writing.md

Examples

Input: /deep-explore "How does the review pipeline work end-to-end?"
Action: Phase 0 → Wave 1 (hooks, skills/review, rules/auto-loop) → Wave 2 (state machine, gate logic) → Report

Input: /deep-explore --areas "hooks, skills/codex-code-review, rules" "Review system architecture"
Action: Phase 0 (user shards) → Wave 1 (3 agents) → Wave 2 (hotspots) → Report

Input: /deep-explore --quick "How does review-state.js work?"
Action: Redirect to /code-explore (small scope)

Input: /deep-explore --agents 2 --waves 2 "Plugin install flow"
Action: Phase 0 → Wave 1 (2 agents) → Wave 2 (2 agents) → Report (max 2 waves)

Signals

GitHub stars
188
Forks
24
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
deep-explore
Source
github.com/sd0xdev/sd0x-harness