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

With no annotations, the description carries the full behavioral burden and does so richly: it discloses that high-confidence active incidents surface automatically unless hidden by an overlapping citation exclusion, that measured-action facts ignore topic filters and have no platform keys, that tracking changes apply only to citations collected from that day on, and that no causal link to metric movements is implied. These are non-obvious traits the agent could not derive from the schema.

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 purpose is correctly front-loaded in sentence one, and little of the text is filler given there is no output schema. But the remainder is a single dense paragraph of backticked field lists and kind enumerations with no segmentation, making it hard to scan and locate a specific fact source.

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?

With no output schema, the description effectively serves as the return-value contract: it enumerates all four fact sources, the discriminated kinds, the exact evidence object shapes, status/resolution semantics, the 0.01 absolute-share floor, and edge cases such as null brandName and null relativeChange. An agent has enough to interpret the payload without further documentation.

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% and the single windowDays parameter (30/90, default 30) is fully documented in the schema. The description adds nothing about the window's effect on results, so the baseline of 3 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?

The opening sentence gives a specific verb and resource ("Get project timeline events") plus the reason it exists ("as context for interpreting Visibility trends"), so the agent knows what it returns and why. It does not, however, name a sibling it should be preferred over (e.g. get_visibility_summary, get_content_changes), so differentiation is left implicit.

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 is only implied through the stated purpose (interpreting Visibility trends); there is no explicit "use this when / not when" and no alternative tool is named despite ~60 siblings covering overlapping visibility, content-change and measured-action data. The agent must infer the call condition.

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