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agy_council_assign_roles

Assign complementary roles to selected participants after project understanding, with clear focus, rationale, and versioned updates for collaborative task execution.

Instructions

After project understanding/reveal, choose complementary roles for this task's selected participants (gpt is client, codex is external), then assign them. Each spec needs role (<=80), focus/output (<=200 each), reason (<=300 UTF-16 units). Initial sources must include all selected initial understandings. Explain choice/tradeoffs in rationale, preserve unresolved differences. No peer endorsement is inferred. Revision needs current expected_role_version, sources and rationale; may update project brief fields. Appends history and generates role prompts, never rewrites old contributions or budgets. Client applies GPT prompt; no new GPT call, model call or automatic turn.

Input Schema

NameRequiredDescriptionDefault
stageYes
rationaleYes
referencesYes
assignmentsYes
discussion_idYes
project_updatesNo
expected_role_versionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.8.0

TDQS

A4.2/5.0
Behavior5/5

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

Adds substantial behavior beyond annotations: appends history, generates role prompts, never rewrites old contributions or budgets, no peer endorsement inferred, and no automatic model/turn is triggered. It also clarifies that the client applies the GPT prompt, which is exactly the kind of side-effect transparency a mutation tool needs.

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

Conciseness4/5

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

Front-loads the core action and precondition, then layers constraints and side effects efficiently. Some sentences are telegraphic ('No peer endorsement is inferred.'), but given the tool's complexity, almost every clause carries needed information.

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?

Adequately covers lifecycle placement, field constraints, side effects and non-effects for a complex nested-parameter mutation tool with no output schema. The main gaps are the shape of assignments and the semantics of stage, which an agent must infer.

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

Parameters4/5

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

Against 0% schema description coverage, the description compensates well: length limits for role/focus/reason, the requirement that sources include all selected initial understandings, and the revision requirements for expected_role_version, sources and rationale. It does not explain the nested assignments structure, the meaning of stage values, or what project_updates may contain.

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

Purpose4/5

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

States a specific verb and resource ('choose complementary roles... then assign them') and ties it to a lifecycle moment ('After project understanding/reveal'). It implicitly distinguishes itself from agy_council_create and agy_council_round via assignment semantics, but it never names those siblings or states the boundary explicitly.

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?

Gives a clear precondition ('After project understanding/reveal') and revision context ('Revision needs current expected_role_version...'), so an agent knows when this call is valid. It stops short of stating when not to use it or naming alternatives among the council tools.

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