find_independent_software

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

No annotations provided, so the description carries the full burden. It discloses ranking by reuse signal, result fields (stars, rank_score), and the author-disjoint filter. It also clarifies it's not citations-based. Doesn't mention side effects, but as a query tool that's 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 paragraph with dashes and parentheticals. It front-loads the purpose but could be more concise. All sentences add value, so it's not wasteful, just stylistically heavy.

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?

With no output schema, it discloses key result fields (stars, rank_score). It covers input constraints and purpose. For a tool with 3 simple paramsaineit is reasonably complete, though the `limit` parameter's behavior is not described.

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?

The description explains `doi` (looks up authors) and `topic` (should be short and broad). `limit` is not explained, though its default 8 implies a count cap. Since schema coverage is 0%, the description partially compensates but not fully.

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's purpose: finding reusable, author-disjoint software for replicating a paper's claim, ranked by reuse signals. It distinguishes itself from citation-based tools and siblings like find_dataset by focusing on code engines. The verb 'find' is explicit and the scope is well-defined.

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?

Provides concrete usage guidance: pass the paper's DOI (authors are looked up) and a short topic, with advice to keep topic broad. It doesn't explicitly contrast with alternatives like find_dataset, but the context makes the use case clear. No when-not-to-use instructions.

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