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

With readOnlyHint already covering the safety profile, the description still adds real context: results are newest-first, the baseline is the first measurement, each check carries what changed since the previous check, and changes are computed deterministically rather than by an LLM. This is substantive disclosure beyond the annotations.

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?

Well front-loaded: the return shape leads, the downstream should not be the first focus, and each sentence carries information. Slightly dense with backticked field names but no wasted sentences.

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?

No output schema exists, so the description must describe return values, and it does so clearly (baseline, monthly checks, numbers, deltas, research_id). It is complete enough to call the tool correctly, with only the sibling-differentiation gap remaining.

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 coverage is 100% and there is one parameter, whose provenance is already documented in the schema ('Project id listed by list_projects'). The description adds no further meaning to the id argument, so the baseline of 3 for high coverage applies.

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) and resource (a followed niche with its history of checks), and details the shape of the payload: baseline plus monthly checks, with numbers and changes. It implicitly distinguishes itself from get_report by routing the agent there for the fresh report, but does not explicitly contrast with siblings like get_research or list_projects.

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?

It gives a useful chain hint ('Pass that research_id to get_report'), which implies this tool is the entry point for reading a project's check history. However, it never states when to use get_project versus get_research, list_projects, or get_report directly, so the routing guidance is only inferred.

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