Perfect Clock

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

Adds real value beyond the annotations: it discloses that the suggested times are persisted for 30 days (explaining readOnlyHint=false) and that a private perfectclock.cc link is returned. Privacy of the link is a useful trust signal. It does not note that repeated calls create additional saved suggestions (relevant to idempotentHint=false), so it falls short of 5.

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?

Two sentences, front-loaded with the core purpose, then the detail about holidays/DST and the returned link. The second sentence is long and dense but every clause (weekends, holidays, DST, 30-day save, private link) contributes information an agent would otherwise lack.

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 correctly takes on the burden of describing results: per-day windows, a suggested start time, and a shareable link. The main remaining hole is the absence of any relationship to plan_meeting_schedule and unexplained days/durationMinutes semantics.

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 67%, and the two undocumented parameters (days, durationMinutes) receive no explanation in the description either. The description implies 'windows' are computed per day and that participants' working hours matter, but adds no format or default guidance beyond what the schema already carries. Baseline 3 is appropriate.

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?

Specific verb plus a precisely scoped resource: it computes the per-day windows where all participants fall inside working hours, plus one best-fit start time. The description is clear enough that an agent knows exactly what it gets back. It never mentions the sibling plan_meeting_schedule, so there is no explicit differentiation, which keeps it at 4.

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?

The clause 'when the time is not decided yet' is a genuine use condition that tells the agent when this tool applies versus scheduling an already-agreed time. No exclusion or named alternative (e.g. plan_meeting_schedule) is given, so the routing decision is left partly to inference.

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

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

Beyond the annotations, the description discloses that the tool expands recurrence into concrete dates, shows local times for every participant, checks working hours, public holidays, and daylight-saving shifts. It also states that the schedule is saved for 30 days and returns a private perfectclock.cc link. These are meaningful behavioral details for a write-capable tool.

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 are front-loaded with the core purpose and then add outcome details without waste. The example is compact and useful. Every sentence contributes to selecting or invoking the tool correctly.

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 seven parameters, nested objects, five required fields, and no output schema, the description is complete enough. It explains what the tool computes, what it saves, and what it returns. No critical invocation or result context is missing.

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 86%, so most parameters are already well documented in the schema. The description adds a helpful example that maps naturally to tz, time, rule, and participants, but it does not add constraints or meaning beyond what the schema provides. Baseline 3 is appropriate when the schema does the heavy lifting.

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 verb and resource: planning one-off or recurring meetings across time zones. The phrase "when its time is known" cleanly distinguishes it from the sibling find_meeting_windows tool, which is for discovering times. An agent can identify the correct tool without opening either schema.

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 clear condition for use: when the meeting time is already known, with a concrete example. However, it does not explicitly name find_meeting_windows as the alternative when the time is unknown. The usage context is strong but not exhaustive.

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