Skip to main content
Glama

peer_plan

Route an implementation planning request with goals, affected modules, and constraints to the optimal peer model for review and collaborative design.

Instructions

Before calling: read relevant source files and attach full contents via files. Pass complete diffs/logs — never prose summaries. Set task with goals, affected behavior, and specific concerns. Route an implementation planning request to the best peer model(s).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesRequired. Goal, success criteria, affected modules, and what 'done' looks like.
repo_pathYesAbsolute path to the repository root the peer should work in (e.g. /home/user/my-app).
constraintsNoHard limits: API compatibility, performance budgets, forbidden approaches, deadlines, out-of-scope.
repo_summaryNoHow the repo is structured today — key modules, patterns, and entry points relevant to this task.
risk_levelNoUse high for auth, payments, migrations, concurrency, and public API changes.
complexityNocomplex when the change spans multiple modules, data paths, or deployment steps.
filesNoChanged source files and binary attachments (screenshots, PDFs). Use correct file extensions for images/PDFs and pass base64 or data-URI content.
idempotency_keyYesStable key for this operation (e.g. review-auth-jwt-1). Reuse the same key when retrying after timeout.
Behavior2/5

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

No annotations are provided, so the description carries full burden. It discloses only that the tool routes to a peer model, but lacks details on side effects, permissions, rate limits, return values, or whether state is modified. This is insufficient for a tool with 8 parameters and no output schema.

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?

Three sentences, concise and efficient. The first sentence sets a precondition, the second gives guidance, and the third states the purpose. However, the core purpose is last, not front-loaded.

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

Completeness2/5

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

Given 8 parameters, 3 required, and no output schema, the description is brief and does not explain return values, error handling, or what happens after routing. It lacks completeness for a planning tool that delegates to another model.

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% with descriptions. The description adds context for `files` (attach full contents, never prose summaries) and `task` (goals, affected behavior), but does not mention other parameters like `repo_path`, `constraints`, `repo_summary`, `risk_level`, `complexity`, or `idempotency_key`. It adds moderate value beyond the schema.

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?

The description clearly states this tool routes an implementation planning request to the best peer model, using verbs like 'Route' and 'planning request'. It distinguishes from sibling tools that focus on asking, debating, or debugging, though it doesn't explicitly differentiate.

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

Usage Guidelines5/5

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

The description provides explicit pre-call instructions: read source files, attach full contents via `files`, pass diffs/logs, and set `task` with goals. It also prohibits prose summaries, offering clear guidance on proper usage.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Rakeen70210/peer-agents-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server