team-research | team-research | ClaudePluginHub

Skill

team-research

From team-research

Dispatches subagents to shallow-scan 3-5 approaches to a problem, get user selection, then deep-dive and consolidate findings. Triggers on 'team research' or similar phrases.

developer-tools

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SKILL.md

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Parent Repo Stars7

Parent Repo Forks0

Last CommitApr 29, 2026

Used By2 plugins

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Tags

subagent-dispatch

approach-evaluation

option-comparison

parallel-research

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Read conversation for problem statement, scope, constraints, success criteria
Signals to read:
- Explicit user description of the problem
- Recent code/files providing technical context
- Stated constraints (budget, timeline, stack, team size)
- Prior approaches already ruled out
- Definition of "good enough" outcome
If problem statement unclear → ask one clarifying question at a time
If structured choices help → use AskUserQuestion with concrete options
MUST state inferred problem statement back to user before any dispatch
MUST get user confirmation on problem statement
MUST NOT dispatch any agent until problem is confirmed

After problem confirmed, dispatch ONE research agent for broad enumeration
Agent names vary by environment; do not assume a specific agent exists
Inspect available subagents via the Agent tool's subagent_type parameter
Pick the available agent whose name/description best matches general research synthesis or broad information retrieval; if multiple candidates fit, prefer the most specific; if none fit, use the most general research-oriented agent available
Shallow agent instructions:
- Enumerate 3–5 candidate approaches only
- One short paragraph per approach — no deep evaluation
- Required output format:
```
1. <Approach Name>
   <One-paragraph description — what it is, how it addresses the problem>

2. <Approach Name>
   ...
```
- Cap response under 300 words
Present shallow-scan output to user verbatim before proceeding

After shallow scan, present results and ask user:
- Which approaches to deep-dive (may pick multiple)
- Whether to add, remove, or reframe any approach
MUST wait for explicit user selection before deep dispatch
MUST NOT infer selection and proceed silently
If user requests a different approach not in list → add it, confirm updated list

Pick one deep agent per selected approach
Agent names vary by environment; do not assume a specific agent exists
Inspect available subagents via the Agent tool's subagent_type parameter
For each selected approach, identify its dominant signal from these categories:
- General synthesis, multi-source aggregation
- Fast targeted retrieval, known-solution space
- Comparative analysis — products, vendors, libraries, options
- Audience sizing, market fit, user demand
- Quantitative datasets, benchmarks, numerical evidence
- Peer-reviewed or scientific evidence
- Emerging-tech trajectory, trend analysis
- Go/no-go pressure-testing, idea validation
For each signal that applies, pick the available agent whose name/description best matches; if multiple candidates fit, prefer the most specific; if none fit, use the most general research-synthesis agent available
MUST always include at least one general research-synthesis agent to anchor the roster
List chosen agent per approach (using its actual subagent_type value) + one-line rationale BEFORE dispatch
Allow user to swap agents if desired

Send single message with multiple Agent tool calls (one per approach)
Each agent receives:
- Original confirmed problem statement
- The specific approach assigned to them
- All known constraints and success criteria
- Output format instruction (see below)
- "Do NOT post findings to any external system. Report in chat only."

Required deep agent output format:

Approach: <name>

Summary: <2-3 sentences>

Pros:
- <point>

Cons:
- <point>

Key Evidence / Citations:
- <source or concrete reference>

Fit Rating: <High / Medium / Low> — <one sentence rationale>

Cap each agent response under 500 words

After all deep agents return, produce consolidated report

Comparison table:

| Approach | Pros | Cons | Fit |
|---|---|---|---|

Conflicts section — where agents cite contradicting evidence; state each side
Recommended approach — prioritized pick with rationale; cite supporting evidence
MUST cite sources where agents returned citations
MUST present report then stop; ask user which direction to pursue
MUST NOT begin implementation

MUST gather and confirm problem context before any agent dispatch
MUST clarify ambiguity before shallow scan
MUST confirm shallow results with user before deep dispatch
MUST dispatch deep agents in parallel (single message, multiple tool uses)
MUST keep all findings local in chat only
MUST NOT post to Slack, GitHub, Jira, or any external system unless user explicitly authorizes
MUST NOT implement chosen approach — recommendation only
MUST NOT proceed through any gate without explicit user confirmation