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

With no annotations provided, the description carries the full disclosure burden. It does add value by disclosing the status vocabulary and the dual-format result (human-readable summary plus machine-readable JSON) delivered once complete. However, it does not disclose what happens while the session is still queued/running — whether partial data is returned, whether the call is non-blocking, or whether a retry/polling pattern is expected. This gap is notable for a status tool whose whole purpose is monitoring in-progress work.

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?

A single dense sentence that front-loads the purpose first, then the status values, then the result format. There is no wasted wording and the structure flows logically from what the tool returns to what the result contains. It could arguably be split for readability, but it earns its place.

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?

For a single-parameter status tool with 100% schema coverage, the description is reasonably complete: it covers both the immediate status output and the eventual result payload. The main missing piece is guidance on behavior for incomplete sessions (e.g., polling semantics), which is partly an artifact of the low complexity here. Given the simplicity of the tool, the gaps are minor.

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 100% — the schema already documents session_id as the identifier returned by run_research. The description adds no parameter-level meaning beyond what the schema provides, so the baseline of 3 applies. The cross-reference to run_research is in the schema, not the description.

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?

States a specific verb ('Returns'), a specific resource ('status of an AI Research session'), and enumerates the exact status values (queued/running/complete/failed). This clearly distinguishes it from the sibling run_* tools, which are all execution/trigger tools, while this is the status-polling companion to run_research. An agent can instantly tell this apart from the execution siblings.

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?

Usage context is implied rather than explicit. The schema description of session_id ('returned by run_research') signals the intended workflow of calling this after run_research, and the sibling list is uniformly run_* execution tools, making the polling role obvious by contrast. However, the description itself never explicitly states 'call this to check progress of run_research' or notes any when-not-to-use conditions, so the guidance remains implicit.

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