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deep-research-team

Deep Research Team orchestrates parallel investigation across multiple researcher agents through a lead coordinator, enabling iterative rounds of targeted inquiry with cross-verification. Use this skill for complex questions requiring multiple research angles, topics where initial findings reveal conflicting claims or gaps, and situations where synthesizing diverse specialist perspectives yields better outcomes than single-agent research.

Install in Claude Code
Copy
git clone --depth 1 https://github.com/malob/nix-config /tmp/deep-research-team && cp -r /tmp/deep-research-team/configs/claude/skills/deep-research-team ~/.claude/skills/deep-research-team
Then start a new Claude Code session; the skill loads automatically.

SKILL.md

# Deep Research Team (Lead Orchestrator)

Conduct thorough, iterative research by coordinating a persistent team of researcher agents across
multiple rounds. This architecture enables mid-investigation steering, targeted follow-up based on
emerging findings, and cross-agent verification.

## Architecture Overview

```
Round 1: Investigation      Round 2: Follow-up          Synthesis

┌──────────┐                  ┌──────────┐                  ┌────────┐
│Researcher│  sends findings  │Researcher│  sends findings  │        │
│    A     ├─────────┬───────>│    A     ├─────────┬───────>│        │
└──────────┘         │        └──────────┘         │        │        │
                     │                             │        │        │
                     v          dispatches         v        │        │
┌──────────┐    ┌────────┐    ┌──────────┐    ┌────────┐    │  Lead  │
│Researcher├───>│  Lead  │───>│Researcher├───>│  Lead  │───>│  synth │
│    B     │    │triages │    │    B     │    │triages │    │  esizes│
└──────────┘    └────────┘    └──────────┘    └────────┘    │        │
                     ^                             ^        │        │
┌──────────┐         │        ┌──────────┐         │        │        │
│Researcher├─────────┴───────>│Researcher├─────────┴───────>│        │
│    C     │  sends findings  │    C     │  sends findings  │        │
└──────────┘                  └──────────┘                  └────────┘
```

**Key principles:**

1. **No peer-to-peer researcher communication.** All coordination goes through the lead. This
   preserves the independence that accounts for 87% of multi-agent gains (Choi et al.) and avoids
   sycophancy failures (Wynn et al.). Researchers never see each other's findings.

2. **Multi-round iteration.** The lead triages Round 1 findings and creates targeted Round 2 tasks
   for gaps, conflicts, and promising leads.

3. **Cross-agent verification (Comprehensive scope).** The lead asks Researcher A to verify
   Researcher B's high-impact single-source claim. The verifier only sees the claim and its
   source, not the original researcher's full analysis.

4. **Dynamic task evolution.** The shared task list starts with pre-planned angles but grows
   organically as follow-up tasks emerge from findings. The lead dispatches follow-up tasks
   directly to specific researchers via SendMessage.

## When to Use

**Use this skill for:**

- Complex questions that benefit from multiple research angles
- Topics where initial findings will reveal what to investigate next
- Research requiring cross-verification of contested claims
- Any question needing synthesis across 5+ sources

**Do NOT use for:**

- Simple factual lookups (use regular web search)
- Questions answerable with 1-2 searches
- Debugging or code questions

## Effort Calibration

| Scope             | Researchers | Rounds | Verification | Model  |
| ----------------- | ----------- | ------ | ------------ | ------ |
| **Focused**       | 2           | 1-2    | None         | sonnet |
| **Broad**         | 3           | 2-3    | None         | sonnet |
| **Comprehensive** | 4           | 3-4    | Cross-agent  | opus   |

Round counts are heuristics, not targets. Stop early when you hit citation convergence --
additional rounds that don't surface new substantive findings waste tokens and context. A
Broad run that converges in 2 rounds is a success, not a shortcut. After each round's triage,
ask: "Would another round change the report's conclusions?" If not, proceed to synthesis.

Default scope is determined by question type (see `references/question-types.md`).
Present the recommended scope to the user and allow override.

**Model selection:**

- **Lead**: inherits user's session model (no override)
- **Researchers**: `sonnet` for Focused/Broad, `opus` for Comprehensive

(Sonnet validated as viable override for Comprehensive when cost matters)

## Output Directory

Research artifacts persist to disk for resumability and backup.

**Directory resolution** -- run this command FIRST, before creating anything. The output is
your `{output_dir}`. Only the fallback branch creates a directory; the others reuse what exists.

```bash
if [ -d "$(pwd)/deep-research" ]; then
  echo "$(pwd)/deep-research"
elif [ -n "$CLAUDE_DEEP_RESEARCH_DIR" ]; then
  eval echo "$CLAUDE_DEEP_RESEARCH_DIR"
else
  mkdir -p "$(pwd)/deep-research"
  echo "$(pwd)/deep-research"
fi
```

After resolving `{output_dir}`, create only the topic subdirectory in Phase 3.

Each session creates a subdirectory: `{output_dir}/{topic-slug}/`

**Contents:**

- `state.md` -- triage checkpoint, cross-references, follow-up plan (written in Phase 4)
- `researcher-{letter}-findings.md` -- backup of each researcher's findings
- `report.md` -- final synthesized report (written in Phase 6)

## Calibrated Confidence Language

Use Kent-style verbal probability expressions in all confidence assessments:

| Term           | Range  | Use When                                  |
| -------------- | ------ | ----------------------------------------- |
| Almost certain | 93-99% | Multiple high-quality sources, no dissent |
| Highly likely  | 80-92% | Strong evidence, minor caveats            |
| Likely         | 63-79% | Good evidence, some gaps                  |
| Roughly even   | 40-62% | Conflicting evidence, genuinely uncertain |
| Unlikely       | 20-39% | Limited or weak evidence                  |

Always pair the verbal term with the probability range in the final report.

## Process

### Phase 0: Classify Question Type

Silently classify the user's question before any interaction.

1. Read `references/question-types.md` for the full taxonomy.
2. Assign a primary type: Factual, Scientific/Health, Consumer, Technical, Opinion/Sentiment,
   Contested, or Emerging/Frontier.
3. For compound questions, decompose into sub-questions and classify each.
4. Note the default scope from the type-to-scope mapping.

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