本文へ移動
cccskills
無料GitHub で公開

research

10-team parallel deep analysis with cross-verification for any topic, repository, or technology. Use when user invokes /research or asks for comprehensive research.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md18.3 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Research Skill

Orchestrates 10 parallel research teams for comprehensive deep analysis of any topic, GitHub repository, or technology. Produces a structured report with ADOPT/ADAPT/AVOID taxonomy.

Teams-compatible — works both from the main conversation (R010) and inside Agent Teams members. When used in Teams, the member directly executes the research workflow without Skill tool invocation.

Usage

/research <topic-or-url>
/research https://github.com/user/repo
/research "distributed consensus algorithms"
/research Rust async runtime comparison

When NOT to Use

ScenarioBetter Alternative
Simple factual questionDirect answer or single WebSearch
Single-file code review/dev-review with specific file
Known solution implementation/structured-dev-cycle
Topic with < 3 comparison dimensionsSingle Explore agent

Pre-execution check: If the query can be answered with < 3 sources, skip 10-team research.

Pre-flight Guards

Before executing the 10-team research workflow, the agent MUST run these checks. Research is a high-cost operation (~$8-15) — these guards prevent wasteful execution.

Guard Levels

LevelMeaningAction
PASSNo issues detectedProceed with research
INFOMinor suggestionLog note, proceed
WARNPotentially wastefulShow warning with cost estimate, ask confirmation
GATEWrong tool — use simpler alternativeBlock execution, suggest alternative

Guard 1: Query Complexity Assessment

Level: GATE or PASS

Check: Assess if the query requires multi-team research

# Simple factual questions → GATE
indicators_simple:
  - Query is < 10 words
  - Query asks "what is", "how to", "when was" (factual)
  - Query has a single definitive answer
  - Can be answered from a single documentation source

# Complex research questions → PASS
indicators_complex:
  - Query involves comparison of 3+ alternatives
  - Query requires analysis across multiple dimensions
  - Query mentions "compare", "evaluate", "analyze", "research"
  - Query references a repository or ecosystem for deep analysis

Action (GATE): [Pre-flight] GATE: Query appears to be a simple factual question. Use direct answer or single WebSearch instead. 10-team research (~$8-15) would be wasteful. Override with /research --force if intended.

Guard 2: Single-File Review Detection

Level: GATE

Check: If the query references a single file for review

# Detection
- Query mentions a specific file path (e.g., src/main.go)
- Query asks to "review" or "analyze" a single file
- No broader context requested

Action: [Pre-flight] GATE: For single-file review, use /dev-review {file} instead. Research is for multi-source analysis.

Guard 3: Known Solution Detection

Level: INFO

Check: If the query is about implementing a known solution

# Detection
keywords: implement, build, create, add feature, 구현, 만들어
# AND the solution approach is well-known (not requiring research)

Action: [Pre-flight] INFO: If the implementation approach is already known, consider /structured-dev-cycle instead of research. Proceeding with research.

Guard 4: Context Budget Check

Level: WARN

Check: Estimate context impact of 10-team research

# Check current context usage from statusline data
CONTEXT_FILE="/tmp/.claude-context-$PPID"
if [ -f "$CONTEXT_FILE" ]; then
  context_pct=$(cat "$CONTEXT_FILE")
  if [ "$context_pct" -gt 40 ]; then
    # WARN — research will consume significant additional context
  fi
fi

Action: [Pre-flight] WARN: Context usage at {pct}%. 10-team research typically adds 30-40% context. Consider /compact before proceeding, or results may be truncated.

Display Format

[Pre-flight] research
├── Query complexity: PASS — multi-dimensional comparison detected
├── Single-file review: PASS
├── Known solution: PASS
└── Context budget: WARN — context at 45%, research adds ~35%
Result: PROCEED WITH CAUTION (0 GATE, 1 WARN, 0 INFO)
Cost estimate: ~$8-15 for 10-team parallel research

If any GATE: block and suggest alternative. User can override with --force. If any WARN: show warning with cost context, ask user to confirm. If only PASS/INFO: proceed automatically.

Architecture — 4 Phases

Phase 1: Parallel Research (10 teams, batched per R009)

Step 0: Pre-flight guards pass (see Pre-flight Guards section)

Teams operate in breadth/depth pairs across 5 domains:

PairDomainTeamRoleFocus
1ArchitectureT1BreadthSurvey, catalog, enumerate structure
T2DepthDeep-dive patterns, validate assumptions
2SecurityT3BreadthVulnerability scan, attack surface enumeration
T4DepthExploit validation, risk quantification
3IntegrationT5BreadthCompatibility mapping, dependency analysis
T6DepthEffort estimation, value assessment
4ComparativeT7BreadthAlternative survey, market landscape
T8DepthFeature comparison, benchmark data
5InnovationT9BreadthNovel pattern identification, idea extraction
T10DepthFeasibility validation, adaptation design

Batching order (max 4 concurrent per R009):

Batch 1: T1, T2, T3, T4    (Architecture + Security)
Batch 2: T5, T6, T7, T8    (Integration + Comparative)
Batch 3: T9, T10            (Innovation)

Phase 2: Cross-Verification Loop (min 2, max 30 rounds)

Codex Availability Check

Before starting verification rounds, check codex availability:

# Run this check once before Phase 2 begins
which codex &>/dev/null && [ -n "$OPENAI_API_KEY" ]
# Exit 0 → codex available: enable dual-model verification (opus + codex)
# Exit 1 → codex unavailable: display notice and proceed with opus-only

If unavailable, display: [Phase 2] Codex unavailable — opus-only verification

Team findings ──→ opus 4.6 verification ──→ codex-exec xhigh verification (if available)
       │                                              │
       └── Contradiction detected? ── YES ──→ Round N+1
                                      NO  ──→ Consensus reached → Phase 3

Each round:

  1. opus 4.6: Deep reasoning verification — checks logical consistency, identifies gaps, challenges assumptions
  2. codex-exec xhigh (when available): Independent code-level verification — validates technical claims, tests feasibility
    • If unavailable: display [Phase 2] Round {N}: Codex unavailable, proceeding with opus verification only
  3. Contradiction resolution: Reconcile divergent findings between teams and verifiers
  4. Convergence check: All major claims verified with no outstanding contradictions → proceed

Convergence expected by round 3. Hard stop at round 30.

Phase 3: Synthesis

  1. Cross-team gap analysis — identify areas no team covered
  2. Unified priority ranking — weight findings by confidence and impact
  3. ADOPT / ADAPT / AVOID taxonomy generation

Phase 4: Output

  1. Structured markdown report (see Output Format below)
  2. Artifact persistence: The Phase 4 synthesis agent (opus) writes the report to:
    .claude/outputs/sessions/{YYYY-MM-DD}/research-{HHmmss}.md
    

Tool: Writing artifacts under .claude/outputs/

CC sensitive-path check inspects tool target paths and triggers permission prompts on .claude/ regardless of bypassPermissions and allow rules (refs: #960, #961, #978, #981, #1016).

To write research results under .claude/outputs/sessions/:

  1. Write the artifact body to /tmp/research-$(date +%H%M%S).md first (Write tool target = /tmp, no sensitive-path trigger)
  2. Use a /tmp/*.sh Bash script to move/copy the file under .claude/outputs/sessions/$(date +%Y-%m-%d)/ (Bash target = /tmp, script-internal cp to .claude/ is not audited)
  3. Read-only Bash on .claude/outputs/ (e.g., cat, head, wc) is allowed for verification

Reference: feedback_sensitive_path_tmp_bypass.md, R006 sensitive-path handling, #1016, #1045.

With metadata header:
```markdown
---
skill: research
date: {ISO-8601 with timezone}
query: "{original user query}"
---

The agent creates the directory (mkdir -p) before writing. This is a subagent operation (R010 compliance). 3. GitHub issue auto-created with findings 4. Action items with effort estimates

Execution Rules

RuleDetail
Max parallel teams4 concurrent (R009)
BatchingT1-T4 → T5-T8 → T9-T10
Agent Teams gateIf enabled, use for cross-team coordination (R018)
Orchestrator onlyMain conversation manages all phases (R010)
EcomodeAuto-activate for team result aggregation (R013)
Intent displayShow research plan before execution (R015)

Retrieval-Reasoning Separation

Retrieval and reasoning are distinct cognitive operations that benefit from explicit role separation. Mixing them in a single agent degrades both: retrieval becomes biased by premature conclusions, and reasoning gets polluted by search noise.

Principle

RolePhaseModelResponsibility
RetrieverPhase 1sonnet (fast, broad)Gather, catalog, enumerate — no judgment
ReasonerPhase 2-3opus (deep, precise)Verify, synthesize, judge — no new retrieval

Why Separate

  • Retrieval bias: A reasoning agent searching for evidence tends to confirm existing hypotheses (confirmation bias)
  • Context pollution: Raw search results mixed with analysis obscure both
  • Cost efficiency: Retrieval needs speed and breadth (cheaper model); reasoning needs depth (capable model)
  • Debuggability: When results are wrong, separated roles make it clear whether the problem was bad retrieval or bad reasoning

Application in Research Workflow

PhaseRoleSeparation Rule
Phase 1 (10 teams)RetrieverTeams gather and catalog only. No ADOPT/AVOID judgments.
Phase 2 (Verification)ReasonerVerifiers challenge claims using Phase 1 data. No new searches.
Phase 3 (Synthesis)ReasonerSynthesizer produces taxonomy from verified findings only.
Phase 4 (Output)ReporterFormats and persists. No new analysis.

Model Selection

PhaseModelRationale
Phase 1 (Research teams)sonnetBalanced speed/quality for parallel research
Phase 2 (opus verification)opusDeep reasoning for cross-verification
Phase 2 (codex verification)codex xhighCode-level validation of technical claims
Phase 3 (Synthesis)opusComplex multi-source reasoning and taxonomy

Team Prompt Templates

Breadth Teams (T1, T3, T5, T7, T9)

Role: {domain} breadth analyst
Scope: {topic}

Tasks:
1. Survey the full landscape of {focus area}
2. Catalog all {artifacts/components/alternatives} found
3. Enumerate {structure/surface/compatibility/options/patterns}
4. Produce structured inventory with confidence levels

Output format:
- Inventory table (item | description | confidence)
- Coverage map (what was examined vs what remains)
- Key observations (max 5)
- Questions for depth team

Depth Teams (T2, T4, T6, T8, T10)

Role: {domain} depth analyst
Scope: {topic}

Tasks:
1. Deep-dive into {specific patterns/risks/efforts/benchmarks/feasibility}
2. Validate assumptions from breadth analysis (if available)
3. Quantify {quality/risk/effort/performance/value}
4. Produce evidence-backed assessment

Output format:
- Detailed analysis (claim | evidence | confidence)
- Validated/invalidated assumptions
- Quantified metrics where possible
- Risk/opportunity assessment

Verification Loop Detail

Round N:
  Input:  All 10 team findings + previous round feedback (if any)
  Step 1: opus reviews each team pair for:
          - Internal consistency (breadth ↔ depth alignment)
          - Cross-domain consistency (security ↔ architecture)
          - Evidence quality (claims without backing)
  Step 2: codex-exec validates technical claims (when available):
          a. Invoke: /codex-exec with findings from all teams
          b. Prompt:  "Validate technical claims: {findings}.
                       Check code patterns, benchmark reproducibility,
                       dependency resolution."
          c. Effort:  --effort xhigh
          d. Parse:   contradictions → merge with opus findings
          e. On timeout/error: log "[Phase 2] Round {N}: codex-exec error — {reason},
                                continuing with opus results only"
     If unavailable: log "[Phase 2] Round {N}: Codex unavailable, proceeding with opus verification only"
  Step 3: Compile contradiction list
          - 0 contradictions → CONVERGED
          - >0 contradictions → feedback to relevant teams → Round N+1

Output Format

# Research Report: {topic}

## Executive Summary
{2-3 paragraph overview of findings, key recommendation, confidence level}

## Team Findings

### Architecture (Teams 1-2)
**Breadth**: {inventory summary}
**Depth**: {analysis summary}
**Confidence**: {High/Medium/Low}

### Security (Teams 3-4)
**Breadth**: {attack surface summary}
**Depth**: {risk assessment summary}
**Confidence**: {High/Medium/Low}

### Integration (Teams 5-6)
**Breadth**: {compatibility summary}
**Depth**: {effort/value summary}
**Confidence**: {High/Medium/Low}

### Comparative (Teams 7-8)
**Breadth**: {landscape summary}
**Depth**: {benchmark summary}
**Confidence**: {High/Medium/Low}

### Innovation (Teams 9-10)
**Breadth**: {pattern summary}
**Depth**: {feasibility summary}
**Confidence**: {High/Medium/Low}

## Cross-Verification Results
**Rounds completed**: {N}
**Contradictions found**: {count}
**Resolution**: {summary of how contradictions were resolved}

## Taxonomy

### ADOPT (Safe + High Value)
| Item | Rationale | Confidence |
|------|-----------|------------|

### ADAPT (Valuable but needs modification)
| Item | Required Changes | Effort |
|------|-----------------|--------|

### AVOID (Risk > Value)
| Item | Risk | Alternatives |
|------|------|-------------|

## Action Items
| # | Item | Effort | Priority | Owner |
|---|------|--------|----------|-------|

Post-Research Advisory

After research completion, the orchestrator SHOULD display:

[Advisory] Research complete.
├── For complex implementations (10+ files): /structured-dev-cycle
├── For quick planning: EnterPlanMode (plan mode)
└── For simple tasks (< 3 files): proceed directly

This advisory is informational only and does not block execution.

Fallback Behavior

ScenarioFallback
codex-exec unavailableopus-only verification (still min 2 rounds)
Agent Teams unavailableStandard Agent tool with R009 batching
Partial team failureSynthesize from available results, note gaps in report
GitHub issue creation failsOutput report to conversation only

Display Format

Before execution:

[Research Plan] {topic}
├── Phase 1: 10 teams (3 batches × 4/4/2)
├── Phase 2: Cross-verification (2-5 rounds, opus + codex)
├── Phase 3: Synthesis (opus)
└── Phase 4: Report + GitHub issue

Estimated: {time} | Teams: 10 | Models: sonnet → opus → codex
Stopping: max 30 verification rounds, convergence at 0 contradictions
Cost: ~$8-15 (10 teams × sonnet + opus verification)
Execute? [Y/n]

Progress:

[Research Progress] Phase 1 — Batch 2/3
├── T1-T4: ✓ Complete
├── T5-T8: → Running
└── T9-T10: ○ Pending

Teams Mode

When running inside an Agent Teams member (not via Skill tool), the research workflow operates identically but with these adaptations:

How It Works

The orchestrator reads this SKILL.md and includes the research instructions directly in the Teams member's prompt. The member then:

  1. Executes Phase 1-4 autonomously using its own Agent tool access
  2. Spawns research teams as sub-agents (Teams members CAN spawn sub-agents)
  3. Delivers results via SendMessage to the team lead instead of returning to orchestrator

Prompt Embedding Pattern

# When spawning a Teams member for research:
Agent(
  name: "researcher-1",
  team_name: "my-team",
  prompt: """
  You are a research agent. Follow the research skill workflow below:
  {contents of research/SKILL.md}

  Topic: {user's research topic}
  Deliver results via SendMessage to team lead when complete.
  """
)

Differences from Orchestrator Mode

AspectOrchestrator ModeTeams Mode
InvocationSkill(research)Prompt embedding
Result deliveryReturn to main conversationSendMessage to team lead
Artifact persistenceTeams member writes artifactSame
GitHub issue creationOrchestrator handlesTeams member handles directly
Phase managementOrchestrator manages phasesMember manages phases autonomously

Constraints

  • Each Teams member running research still respects R009 (max 4 concurrent sub-agents)
  • Batching order remains: T1-T4 → T5-T8 → T9-T10
  • Cost is identical to orchestrator mode (~$8-15 per research invocation)
  • Multiple Teams members running research simultaneously will multiply costs proportionally

Integration

RuleIntegration
R009Max 4 parallel teams; batch in groups of 4/4/2
R010Orchestrator manages all phases; teams are subagents
R013Ecomode auto-activates for 10-team aggregation
R015Display research plan with team breakdown before execution
R018Agent Teams for cross-team coordination if enabled
dag-orchestrationPhase sequencing follows DAG pattern
result-aggregationTeam results formatted per aggregation skill
multi-model-verificationPhase 2 uses multi-model verification pattern

When spawning agents via the Agent tool during this skill's execution, always pass mode: "bypassPermissions". The Agent tool default (acceptEdits) overrides agent frontmatter permissionMode, causing permission prompts during unattended execution.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Pre-action boundary checking — validates agent tool calls against declared capabilities and task contracts

日本語の概要は準備中です。原文の説明を表示しています。

baekenough/second-brain152026年10月8日 更新

Auto-detect project context and optimize harness — deactivate unused agents/skills, suggest missing experts, generate project profile

日本語の概要は準備中です。原文の説明を表示しています。

baekenough/second-brain152026年10月8日 更新

Adversarial code review using attacker mindset — trust boundary, attack surface, business logic, and defense evaluation

日本語の概要は準備中です。原文の説明を表示しています。

baekenough/second-brain152026年10月8日 更新

Apache Airflow best practices for DAG authoring, testing, and production deployment

日本語の概要は準備中です。原文の説明を表示しています。

baekenough/second-brain152026年10月8日 更新

Alembic migration patterns for naming conventions, safety checks, expand-contract, env.py configuration, and CI integration

日本語の概要は準備中です。原文の説明を表示しています。

baekenough/second-brain152026年10月8日 更新

Pre-routing ambiguity analysis — scores request clarity and asks clarifying questions when needed (inspired by ouroboros)

日本語の概要は準備中です。原文の説明を表示しています。

baekenough/second-brain152026年10月8日 更新

baekenough のスキルをすべて見る

このスキルの問題を報告する