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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds value beyond that by disclosing the payload shape (cost-to-start, per-minute call cost for voice-agent, paste-ready AGENTS.md brief), which matters because there is no output schema. It does not say how an unrecognized slug is handled.

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?

Two sentences, front-loaded with what the tool returns before the slug inventory. The content block is dense with nested parentheticals ("APIs per part (free tier, price, official MCP server and its card)") and the slug list is long, but both earn their place as payload preview and enum substitute.

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?

For a single-optional-param read tool with no output schema, the description is largely sufficient: it explains the return contents and lists valid inputs. The missing piece is the relationship to list_recipes and design_recipe, which an agent needs in order to route correctly in a 20-tool catalog.

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 coverage is 100%, so the baseline is 3. The description goes further by enumerating the nine valid slugs (rag-assistant, voice-agent, ai-chatbot, support-agent, research-agent, telegram-ai-bot, data-analyst-agent, solana-bot, prompt-to-video), effectively supplying an enum the schema lacks and clarifying that fuzzy words like "voice agent" map to a slug.

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 uses a concrete framing ("the parts for one kind of AI product") and then enumerates exactly what a recipe returns: APIs per part, model per price tier, libraries, skills, coding agents, startup cost and an AGENTS.md brief. That is far more specific than the title alone. It stops short of naming the sibling it differs from (list_recipes, design_recipe), so an agent must infer the boundary itself.

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?

It gives one explicit usage rule — "Call with no arguments to list them" — which is genuinely actionable for discovery. But with three related siblings (list_recipes, design_recipe, plan_project) present, there is no statement of when to pick this tool over them, and no guidance on what happens with an unknown slug.

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