compose_prd_parse

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

With no annotations provided, the description carries full burden. It discloses that the tool does not call any LLM ('Pure-MCP'), that it builds a prompt and JSON schema, and includes existing tasks. It does not describe any side effects like file modifications or network calls, which is fine for a tool that only generates a prompt. However, it could be more explicit about whether it modifies any state.

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

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

The description is extremely concise—only three sentences—yet conveys all essential information about purpose, non-LLM nature, workflow, and deduplication feature. Every sentence adds value, no fluff.

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

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

Given the tool's complexity (4 parameters, no annotations, no output schema), the description lacks parameter explanations. It does well to explain the workflow and deduplication, but without parameter semantics, the agent may struggle to invoke it correctly. The description is incomplete for a tool with this many inputs.

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

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

Schema description coverage is 0% and the description does not explain any of the 4 parameters (workspace_root, prd_text, max_tasks, include_existing). The description provides context about the workflow but gives no details about what each parameter means or how they affect output. This is a significant gap.

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

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

The description clearly states the tool builds a prompt + JSON schema for decomposing a PRD into atomic tasks. It explicitly distinguishes itself from calling an LLM ('Pure-MCP: does NOT call any LLM') and differentiates from the sibling tool 'record_tasks' by describing the workflow where the host uses this tool's output then calls record_tasks.

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

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

The description provides clear guidance on when to use the tool: to decompose a PRD. It explains the workflow (caller feeds prompt to its LLM, then calls record_tasks). While it doesn't explicitly state when not to use it, the context is sufficient. The mention of 'includes existing tasks' prevents duplication, which is a usage hint.

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