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

Annotations already cover readOnlyHint=true and openWorldHint=false, so safety is handled. The description still adds genuine value with the pricing model (B1, $0.01/call, included in Understanding and Influence) and a pointer to apis://prices, which the agent cannot learn from structured fields.

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 purpose is front-loaded and most sentences carry real information. However, the 'Understanding.' fragment is an awkward orphan sentence, and pricing/commercial framing sits in the middle of the functional description where it interrupts flow; a trimming pass would help.

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?

With no output schema, the description correctly takes on the burden of describing the return shape — rows of providers per layer/capability with evidence gradings, sources, and MCP status. That is sufficient to call it correctly, though nothing is said about result size or whether the full blueprint is always returned.

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 schema baseline is 3. The description goes further by explaining what the evidence tiers actually mean (rows 'graded declared, observed or inferred, with its sources'), which gives meaning to the min_tier enum, and it clarifies the category parameter with a worked example (crm-sales) and the shared-layer special value.

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 names a specific resource and then defines precisely what it contains: catalog providers that a category's leading apps integrate with, grouped by stack layer and capability, each row graded declared/observed/inferred with sources and MCP status. This level of specificity makes it unmistakable against siblings like get_provider_apis or recommend_stack.

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 offers one concrete routing hint — 'Use shared-layer as the category for the providers most categories share' — but that is parameter guidance rather than tool-selection guidance. There is no statement of when to prefer this over alternatives such as get_capability_edges, gap_analysis, or recommend_stack, so the agent must infer the fit.

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