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

Annotations already establish this is a non-read-only, non-destructive write (readOnlyHint=false, destructiveHint=false), and the description's 'Record/Log' verbs align with that. The description adds genuine value beyond annotations by disclosing the downstream behavioral consequence: events are overlaid on analytics and affect how future numbers are interpreted. It does not, however, disclose editability (an update_project_event sibling exists), idempotency, or what a successful log returns.

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?

Three sentences, roughly 70 words, with zero filler: action + examples, purpose, then the when-to-log trigger. The concept is front-loaded and every sentence earns its place. This is exemplary conciseness for a tool of this complexity.

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?

Given no output schema, 12 parameters, and a fuzzy-resolved 'project' parameter, the description covers the conceptual 'what/why' well but leaves invocation gaps. It does not clarify how to select among the relational identity parameters, what a good title vs description looks like, or what confirmation the agent should expect. Adequate at the concept level, incomplete at the call level.

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?

With only 33% schema description coverage across 12 parameters, the description bears a heavy duty to compensate, and it only partially does. The examples map usefully onto the category enum (outage→incident, campaign launch→launch, external algorithm update→external) and 'happened on a date' mirrors occurred_on, but the required title parameter is never explained, and the overlapping identity params (client/client_id, project/project_id, task_id) are left to the agent to disambiguate.

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 states a specific action and resource ('Record something significant that happened on a date') backed by concrete examples (budget change, site migration, outage). It also explains the underlying purpose ('overlaid on analytics later so the data can be read correctly'), which goes well beyond a tautology. However, it never explicitly distinguishes itself from sibling logging tools like log_project_issue or log_project_decision, so the differentiation is implicit rather than stated.

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?

Provides a clear positive trigger condition: 'Log one whenever you make or observe a change that will show up in future numbers.' This tells an agent when to act without ambiguity. It lacks the other half of strong guidance — explicit when-not-to-use and named alternatives — so it falls short of a 5.

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