firecrawl_research_related_papers

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

Annotations show readOnlyHint=true, destructiveHint=false, which the description matches (it's a read-only expansion). The description adds useful behavioral context: internal multi-round re-seeding for similar mode, and that it returns candidates plus pool size. No contradictions.

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 front-loaded with the core action and is dense with valuable information. Every sentence adds necessary context, and there is no redundancy or fluff.

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?

Given 5 parameters and no output schema, the description adequately covers purpose, input, modes, behavior (internal expansion), and output (candidates + pool size). It addresses all essential aspects for correct tool selection and invocation.

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 0%, but description explains seed_ids (pass arXiv ids of strongest hits), intent (natural-language intent), and mode (three modes with definitions). It hints at output but does not cover k or rerank. This adds significant meaning for key parameters, compensating for lack of schema descriptions.

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 clearly states the tool expands from anchor papers via citation graph, ranked and filtered by natural-language intent. It specifies input (arXiv ids as seed_ids) and modes (similar, citers, references). It distinguishes itself from plain search by reaching papers that would be missed, and from siblings like firecrawl_research_search_papers.

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?

The description advises using the tool on best hits before finishing, and explains that a single similar call already runs deep expansion internally, so chaining many is unnecessary. However, it does not explicitly mention when not to use it or provide alternatives, though it contrasts with plain search.

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