WhenMeet.me — group scheduling

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

Description details the write action (calendar, email, share URL) and requires authentication. Annotations indicate readOnlyHint=false, so no contradiction. Adds context beyond annotations, though idempotency or failure modes aren't covered.

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 description is a single sentence that front-loads the main action and efficiently conveys all key details with no unnecessary words.

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?

The description explains the outcome (share URL, email invites) and authentication. Although it lacks error handling or edge cases, it provides sufficient context for typical usage given the schema covers parameters.

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 67%, so the schema already documents most parameters. The description does not add extra meaning to parameters beyond the schema. No improvement or harm.

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 clearly states the tool confirms a meeting by writing to the host's calendar, optionally adding a Google Meet/Teams link, emailing invites with ICS attachment, and returning a share URL. This distinguishes it from sibling tools like suggest_time or find_common_slots.

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 description implies usage context (after planning) and states authentication requirement, but does not explicitly specify when to use or avoid this tool compared to siblings. No alternatives or exclusions are mentioned.

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?

Annotations declare readOnlyHint=true, and the description adds significant behavioral details beyond that: merging live data, scoring, buffer time, timezone handling, return format (up to 8 slots with allFree/compromise). No contradiction, and the description enriches agent understanding.

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 description is well-structured: starts with main purpose, adds key behavioral details, ends with defaults and auth requirement. It is succinct without unnecessary repetition.

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 complex tool with 5 parameters and no output schema, the description covers scoring logic, constraints, return format, and authentication. It lacks minimal details like error behavior, but is adequate for selection and invocation.

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 description adds extra context like default window of 14 days, timezone fallback role, and that the authenticated user should be included as host. This goes beyond the schema's basic descriptions.

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 uses a specific verb 'Rank' and specifies the resource 'meeting times for given participants', clearly distinguishing from siblings like 'suggest_time' by mentioning merging multiple data sources (calendar, manual, heat-map).

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 explicit context on when to use (finding best meeting times) and includes details like filtering Mon-Fri waking hours, scoring in timezones, buffer time, and authentication. Does not explicitly state when not to use or contrast with alternatives like 'suggest_time', but the context is clear.

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?

Annotations already declare readOnlyHint=true, indicating safe read-only behavior. The description adds useful context by specifying 'hand-marked free slots', but does not elaborate on other behavioral traits like response format or pagination. It is consistent with 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?

The description is a single sentence that conveys the core purpose without unnecessary words. Every part carries meaning, and it is appropriately front-loaded.

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 the complexity (3 required parameters, no output schema, and sibling tools), the description is minimal. It does not explain the return format, behavior when no slots exist, or how this relates to other availability tools. It is adequate but could be more complete.

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 0%, so the description must compensate. It mentions 'for an email within a window', which loosely connects to the email, from, and to parameters, but does not specify data types or format (e.g., timestamps). The description adds some meaning but not full semantics.

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 clearly states the tool reads previously hand-marked free slots for an email within a window. It specifies the verb 'Read', the resource 'previously hand-marked free slots', and the context 'for an email within a window', which distinguishes it from siblings like 'set_manual_availability' (write) and 'get_meeting_availability' (likely computed).

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 description implies usage for retrieving manually set free slots, providing clear context that the slots are hand-marked rather than automatically computed. It does not explicitly list exclusions or alternatives, but the sibling list (e.g., 'get_meeting_availability') provides some differentiation.

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?

Annotations already declare readOnlyHint=true, and the description confirms it reads data without side effects. It adds value by detailing the returned fields (time, title, conference URL, host, alternate times), which is beyond the annotation scope.

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 description is a single, well-structured sentence that front-loads the action ('Read a meeting') and efficiently conveys essential details about input and output. No extraneous words.

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 the low complexity (one parameter, no output schema, annotations present), the description provides all necessary information: input format, output fields, and read-only behavior. It is sufficiently complete for an agent to use the tool correctly.

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?

The only parameter, meetingId, is explained in the description as 'the share-link id (the UUID from /m/<id>)'. Since schema description coverage is 0%, the description fully compensates by adding semantics that are missing from the input schema.

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 clearly states the tool reads a meeting using its share-link ID, specifying the fields returned (time, title, conference URL, host, alternate times). This differentiates it from sibling tools like create_meeting or get_meeting_availability, making its purpose obvious.

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 description mentions the input format (UUID from /m/<id>) and the fields returned, providing clear context for its use. However, it does not explicitly state when not to use it or compare it to alternatives, though the purpose is self-evident.

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?

The description adds transparency beyond the readOnlyHint annotation by stating that individual calendars are never exposed and explaining the scoring logic (buffer, soonness). This is valuable context for the agent's decision-making.

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 description is a single paragraph that efficiently communicates key points without excessive length. It is front-loaded with the main purpose and then adds details, though it could be slightly more structured.

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 5 parameters, no output schema, and only a readOnlyHint annotation, the description provides good behavioral context (non-exposure, auth) and some output details, but lacks parameter guidance and a structured return format description. It is adequate but not fully complete.

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 only 40%, and the description does not add meaning to parameters like 'tz', 'durationMin', or 'meetingId'. It mentions 'per-30-min-slot' (output) but not input parameters. For 5 parameters, this is insufficient compensation.

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 clearly states the tool aggregates availability for an existing meeting, with specific output details (per-30-min slots, ranked slots, allFree). It distinguishes itself from siblings like 'get_manual_availability' by focusing on existing meetings and aggregated results.

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 description notes that no authentication is needed and the meeting ID is the capability, which is a security guideline. However, it does not explicitly state when to use this tool versus alternatives like 'find_common_slots' or 'get_manual_availability', nor does it provide exclusions or when-not-to-use scenarios.

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 readOnlyHint=false annotation, the description discloses that accepting moves the meeting and re-sends invites. It also states authentication requirement, adding behavioral context.

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, no redundant information. Front-loaded with the core action and quickly adds critical behavioral details.

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 the tool's simplicity and lack of output schema, the description covers the main purpose and constraints. Minor gaps like what happens on decline are implied but acceptable.

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 0% schema description coverage, the description partially compensates by explaining the action parameter's effect. However, meetingId and suggestionId are not defined beyond their names, leaving some ambiguity.

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 clearly states the tool accepts or declines a proposed alternate time and explains the effect of accepting. It distinguishes itself from siblings like suggest_time by focusing on the response step.

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?

Description explicitly notes only the meeting host may call and requires authentication, providing clear usage constraints. It does not compare to alternatives but the context is sufficient.

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?

The description discloses key behaviors: it replaces previously marked slots within a window and updates the group heat-map immediately. It also explains authentication requirements and the conditional need for a Turnstile token. The annotation readOnlyHint=false is consistent with this write operation.

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 description is concise (two sentences) and front-loaded with the core purpose. Every sentence adds essential information without redundancy or fluff.

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?

Despite having no output schema, the description explains the impact (replaces slots, updates heat-map) and authentication nuance. It covers the essential context for a tool with 5 parameters and a fallback use case. Minor gap: no mention of what the response looks like or if there's any confirmation.

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?

The schema coverage is 60%, but the description adds meaning to several parameters: windowFrom and windowTo are identified as Unix ms timestamps, freeSlots as an array of objects with start and end, and turnstileToken's requirement is explained conditionally. Email and the structure of freeSlots items beyond start/end are not described, but the description adds value beyond the schema.

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 clearly states the verb 'publish' and the resource 'hand-marked FREE time slots for an email address', and distinguishes it as a 'no-calendar fallback' for users like Apple iCloud. This differentiates it from sibling tools such as create_meeting or get_manual_availability.

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 description provides context on when to use the tool (fallback for non-calendar users) and explains that authenticated callers skip the bot challenge while anonymous callers may need a Turnstile token. However, it does not explicitly state when not to use it or compare it to alternatives beyond the fallback scenario.

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?

Discloses write nature (proposing time, host notified), conditional auth requirements, and Turnstile token. No contradiction with annotations (readOnlyHint=false).

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 with the main action first, followed by necessary details on authentication and notification. No redundant information.

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?

Covers purpose, auth flow, callback (host notified), and conditional parameter. No output schema needed as effect is described. Sufficient for selection and invocation.

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?

Adds context to parameters: meetingId is for existing meeting, time parameters are unix timestamps, turnstileToken is for anonymous callers. Schema covers 67% with descriptions; description fills gaps and explains flow.

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?

Describes a specific action: proposing a different time for an existing meeting on behalf of a guest. Clearly distinguishes from sibling tools like create_meeting or find_common_slots.

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?

States when to use: to propose a new time. Provides context on authentication requirements and host notification. Does not explicitly exclude alternatives but is clear enough.

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