list_winning_submissions

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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals that only publicly announced winners are returned, that past editions are preferred, and lists the return fields. However, it does not clarify whether the operation is read-only, if authentication is needed, or how 'prefer' affects results (e.g., fallback behavior). This is adequate but not rich.

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, front-loaded with the primary purpose and supplemented by a terse second sentence covering usage nuance and return fields. No waste, no redundancy, ideal size.

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 has a single parameter, an output schema (signaled), and a simple listing purpose. The description covers the key behavioral context (public availability, past editions, return contents) and is sufficient for the likely use case. It does not explicitly differentiate from all sibling tools, but within this context it is largely complete.

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 schema provides only a parameter name (hackathon_id) with no description (coverage 0%), so the description must compensate. It does add meaning by tying the parameter to 'a hackathon' and advising to prefer past editions, which informs the choice of hackathon_id. However, it does not explain the format, source, or how to obtain the ID, so it only partially compensates for the schema 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 lists publicly announced winners/awarded submissions for a hackathon, with a specific verb ('List') and resource ('winning submissions'). It also distinguishes itself by mentioning the specific return fields (award, placement, win_signals, links), which differentiates it from broader submission-listing tools like extract_public_submissions.

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 gives clear usage context by advising to prefer past (ended) editions, which guides the agent to use this tool for historical hackathons rather than ongoing ones. It does not explicitly name alternatives or exclusions, but the sibling names (e.g., extract_public_submissions) imply a contrast. This warrants a 4, as it provides context but no explicit when-not-to-use.

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