paper_citation_graph

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

No annotations provided, so description carries full burden. Discloses data source (Semantic Scholar API), recursive fetching behavior (depth levels explained), output format (Mermaid + JSON), and rate-limiting hints via max_per_level. Missing explicit error behavior or auth requirements.

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?

Clear Args/Returns structure with logical flow. Chinese text is appropriately concise; no redundant sentences. Minor deduction for Returns section listing output fields that may duplicate output schema details, though helpful given context.

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 complex graph-generation tool with zero schema coverage, description adequately covers inputs, data source, and output structure (nodes/edges/statistics). Sufficient since output schema exists to handle return value specifics.

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?

With 0% schema description coverage, the description fully compensates by documenting all 3 parameters: doi with example syntax, depth with semantic meanings (1=direct, 2=secondary), and max_per_level with clear quantity 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?

Description uses specific verb '生成' (generates) + resource '论文引用图谱' (paper citation graph) and explicitly distinguishes from siblings via the Mermaid visualization and Semantic Scholar API sourcing—unique traits not shared with paper_search or paper_download.

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?

Implies usage through functional description (use when needing citation visualization), but lacks explicit 'when to use vs alternatives' guidance comparing to siblings like paper_ai_analyze or paper_search.

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