works_by_effect

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

With no annotations, the description carries the full burden and does so: it enumerates the three per-effect outcomes (found / same_name / not_on_homepage) with precise meanings, and explicitly warns that same_name is a different effect_id and must not be treated as the same effect. It also discloses cost (one to two requests per effect, about 6 seconds for 20), which fields are usable downstream (template_id), and the critical lifetime constraint that image/video/audio refs are only valid for the duration of this MCP run.

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 and the outcome enumeration are front-loaded, and the operational notes (cost, ref lifetime) are pushed to the end where an agent can skim them. Sentences are dense rather than padded, though the closing paragraph about *_ref handles and image_view is a slight tangent relative to the core lookup and could have been one clause shorter.

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?

There is no output schema, so the description must explain returns, and it does: status semantics per effect, that found and same_name works appear in items with works_list-compatible fields, that template_id feeds works_download / works_open, and how media refs are encoded and consumed via image_view. For a four-parameter, batched, no-output-schema tool, nothing an agent needs to call it correctly is missing.

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 real meaning the schema does not: it justifies the category_id default (推荐 is the only category that reliably resolves ID lookups across categories) and explains the batch bound in domain terms (max 20 = one rank page) plus what the optional name field enables (same-name fallback). It adds context beyond the field-level descriptions rather than repeating them.

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 opens with a specific verb and resource: look up whether the homepage has a project (工程) for a given effect ID, and states it is the same backend as the homepage search box's 特效ID search. It also names the upstream sources of the ID (rank_list / rank_subjects / rank_innovation effect_id) and the downstream consumers (works_download / works_open via template_id), so an agent can position it against siblings without opening other schemas.

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 an explicit default (query in 推荐, so category_id is usually unnecessary) and explains why: querying by ID in 推荐 also finds works that only appear in other categories, whereas querying by ID in another category can miss them. That is actionable when-to guidance plus a concrete exclusion. It stops short of naming a specific sibling as an alternative (e.g. works_search or effect_check), so it is not a full when/when-not/alternatives statement.

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