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

With no annotations, the description does the important work itself: it discloses the auth requirement (Bearer API key) and, critically, that calls consume credits — a cost signal an agent can't infer from the schema. It stops short of return shape, credit cost magnitude, rate limits, or error behavior.

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?

Three short sentences, zero filler, purpose first followed by the two hard constraints (auth, credits) and the prerequisite call. Nothing is wasted.

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 generic dispatcher with a nested free-form params object, no annotations, and no output schema, the description leaves the return shape and the relationship to the per-platform siblings unexplained. The auth/credit/discovery facts are covered, but an agent still has to guess why it would use lookup instead of instagram_user.

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, but the description adds meaning the schema cannot: valid platform/resource values and the free-form params keys must be resolved via list_endpoints, and none of the parameters have enums in the schema. That discovery dependency is genuinely useful parameter semantics.

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 verb and resource ('Fetch public social data via Socify') are stated, but 'social data' is so broad that it doesn't distinguish this tool from any of its ~40 platform-specific siblings (instagram_user, tiktok_posts, youtube_search). It never says this is the generic/parameterized dispatcher versus the pre-bound per-platform tools, so an agent can't confidently choose it.

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 concrete workflow rule: call list_endpoints first to discover platform/resource/params. That is real guidance. But there is no statement of when to prefer lookup over the many specific siblings, nor any exclusion, which is the key routing decision for this tool.

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