PDS IP 核查询

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

With no annotations provided, the description carries full behavioral burden. It discloses what each call mode returns, that category uses substring matching, that all-args-omitted produces a summary, and that every core includes a datasheet PDF path. It omits error/edge-case behavior, but for a read-only lookup this is acceptable.

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 a single dense sentence with semicolon-separated modes, front-loaded with scope ('~65 核') and a representative list of categories. Every clause conveys either a mode, its behavior, or its output; there is no filler.

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?

It covers slug, query, category, and the empty-args case, and describes output contents adequately. However, the schema exposes a 'mode' parameter with auto/keyword/semantic options, and the description does not explain when to choose semantic over keyword, nor what 'auto' resolves to. Without an output schema, those ambiguities remain, so completecess is slightly short.

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 100%, so the baseline is 3. The description adds meaningful semantics beyond the schema: e.g., slug returns the core's header/params/PDF, category is a substring match, and passing no filter returns a summary list. This extra behavioral nuance is valuable and justifies the score.

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 states a specific action ('查') and a concrete resource ('PDS IP 目录'), and further distinguishes itself by enumerating output contents (header, supported devices, parameters with enum options, datasheet PDF path, summary list). This clearly separates it from sibling lookup tools like fpga_primitive_lookup or fpga_doc_search.

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 explicit usage conditions for each mode: slug for exact matching, query for keyword recall, category for substring filtering, and no-args for a summary list. This is strong operational guidance. However, it does not explicitly compare this tool to sibling tools or state when not to use it, so the cross-tool selection logic is left to inference.

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