list_open_hypotheses

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

With no annotations, the description carries the burden. It discloses the operation type (listing), ordering by confidence, and inclusion of linked concepts, but does not explicitly state read-only safety, sorting direction, or potential side effects. It is adequate but not thorough.

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 well-structured, with a clear purpose statement upfront, followed by concise usage guidance and a compact Args/Returns section. Every sentence earns its place, and there is no redundancy.

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 simple (one optional parameter, output schema present). The description covers purpose, usage, parameter meaning, and return format. Minor gaps like sorting direction do not significantly hurt completeness given the simplicity and existing output schema.

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 description coverage is 0%, and the description fully compensates for the only parameter by explaining 'limit' as 'Maximum number of hypotheses to return.' This adds clear meaning beyond the schema's type/default, though it could be more detailed.

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 immediately states a specific verb ('List') and resource ('open (unresolved) hypotheses') with clear scope and ordering. It distinguishes this tool from siblings like record_hypothesis or find_bridges by focusing on listing existing unresolved hypotheses.

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?

Two explicit use cases are given: reviewing pending hypotheses for bench verification and finding hypotheses related to a current issue. However, it does not mention exclusions or name alternative tools, so it stops short of full guidance.

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