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Squad Research

squad_research

Investigates a research question or codebase to gather evidence and inform planning. Routes to the squad's researcher agent for exploration.

Instructions

Run the squad's research stage on a question or codebase. Routes to the Task Researcher (squad researcher role) at the auto, parallel-eligible tier to investigate, explore, and gather evidence before any plan or change. Delegated execution: returns the Squad Coordinator persona, the matched routing row, and a framed dispatch request; the calling host runs the subagent loop. Use for "research", "investigate", "explore", or "find out" requests.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoOptional autonomy mode for the turn (autonomous validator loop or autopilot pipeline).
tierNoOptional model-tier hint overriding the coordinator's cost-first default.
ownerNoOptional Member Name from team.md to pick a specific named member.
squadNoOptional federation sub-squad to target (state under .copilot-tracking/squad/members/<name>/); omit outside a federation.
contextNoOptional free-form context (files, constraints, prior findings) to frame the request.
profileNoOptional squad profile to seed when the project has no squad yet.
requestYesThe research question or topic for the squad this turn.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses the delegated execution pattern, return structure (Squad Coordinator persona, routing row, dispatch request), and the subagent loop responsibility. However, it does not explicitly state if the tool is read-only or requires permissions, though the research context implies non-destructiveness.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, followed by concise execution details and usage hints. Every sentence adds value, with no fluff. It is well-structured and easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given seven parameters (one required), no output schema, and no annotations, the description covers the execution flow, return format, and intended usage. It does not explain return value types in detail, but the description of the return structure is sufficient for the agent to understand what to expect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds minimal parameter context beyond what the schema provides (e.g., 'free-form context' for the context parameter). It does not deep-dive into any parameter, so no extra value beyond the baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool runs the squad's research stage on a question or codebase, using a specific researcher role. It explicitly distinguishes from sibling tools by noting it occurs 'before any plan or change', making its purpose unique and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit trigger keywords ('research', 'investigate', 'explore', 'find out') and context (before planning). It implies when not to use (not for planning/architecting) but does not explicitly list alternatives, leaving some room for ambiguity.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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