find_code_repo

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

No annotations are provided, so the description carries the full burden. It discloses the algorithm: scanning for GitHub URLs and using a Papers With Code fallback. This is meaningful behavioral transparency beyond just 'finds a repo.' It also hints at a potential outcome ('if any'), implying it might not always find a repo. However, it does not mention limitations like other repo hosts or what happens when a paper is not on arXiv. Still, the strategy is a strong disclosure of internal behavior.

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 two sentences with zero fluff. The first sentence states the purpose clearly and the second provides the strategy. It is front-loaded with the core action, and every word contributes value. The structure is efficient and easy to parse.

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?

The tool is relatively simple with one parameter and an output schema, so the return format is presumably covered by the output schema. However, the input parameter is not described, which is a critical gap. The description explains the method but leaves the agent unsure what to pass as input_str. Given the lack of annotations, the description must carry more weight, and this omission makes it incomplete.

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 input schema has one required parameter, 'input_str', with no description and 0% schema description coverage. The description refers to 'a paper' but does not explain what input_str should contain (e.g., a paper ID, URL, or title). It does not clarify the expected format or how the tool will use it. The description fails to compensate for the lack of schema detail, leaving the agent uncertain about the parameter's meaning. This is a significant gap.

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: 'Discover the code repo (if any) associated with a paper.' It uses a specific verb ('discover') and resource ('code repo'), and the scope is clear. This distinguishes it from siblings like get_paper_metadata or assess_repo_reproducibility, which handle metadata or reproducibility assessment. The strategy also clarifies the exact function.

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 implies when to use it: whenever you need to locate a paper's code repository. It provides a concrete strategy (scanning full text/abstract for GitHub URLs, falling back to Papers With Code for arXiv papers), which gives context on its operation. It does not explicitly exclude scenarios or name alternative tools, but the purpose is clear enough that an agent would know it is the right tool for finding code repos. Lacks explicit 'when not to use' guidance, so a 4 is appropriate.

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