MeetingPoll — Fast Group Scheduling & Availability Polls

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

Beyond the annotations, the description discloses that it creates a live backend record, requires no authentication for public initiation, and is rate-limited to 60 requests per minute per IP. This adds concrete side-effect, auth, and rate-limit context that annotations alone do not provide.

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 front-loaded, but the description contains avoidable redundancy: 'Agentic tool' is filler, the 'when to use' sentence restates the tool name, and the parameter list duplicates the schema. It is usable but not tightly written.

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 an eight-parameter mutation tool with no output schema, the description covers purpose, alternatives, side effects, auth, rate limits, and return shape. The return description is somewhat generic, but the critical operational context is present.

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%, so the input schema already documents all eight parameters including required/optional status. The description lists the parameters but adds no format, validation, or behavioral meaning beyond what the schema provides, so 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?

The first sentence states a specific verb and resource: create a new meeting scheduling poll with candidate dates, time slots, duration, and invitee emails. It also names the sibling tools it is not, so an agent can distinguish it from get_poll_consensus and submit_participant_vote without inspecting schemas.

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 explicitly says not to use this tool when another specialized tool fits better and names get_poll_consensus and submit_participant_vote as alternatives. The 'when to use' sentence is circular, but the purpose sentence plus exclusions provide clear enough routing context for an agent.

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 readOnly, idempotent, non-destructive, and open-world behavior. The description adds meaningful operational context: public unauthenticated access and a rate limit of 60 requests per minute per IP. It also restates zero state mutation, but the added auth and rate-limit details earn credit 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?

The opening analytical sentence is well front-loaded, but the definition contains boilerplate: the 'when to use' clause repeats the tool name, the parameter line duplicates the schema, and the return sentence is generic ('matched records or computed metrics') rather than tailored to consensus analysis.

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 one-parameter read-only tool with no output schema, the definition covers purpose, alternatives, safety/auth/rate-limit behavior, and a high-level return description. It is complete enough for correct invocation, though the return description remains generic.

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 poll_id parameter is fully described in the schema. The description only repeats that poll_id is required, adding no syntax or format detail beyond the schema; baseline 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 first sentence names a specific analytical action—analyzing vote distribution and calculating the optimal meeting slot—and enumerates concrete outputs such as percentage agreement, voter breakdown, and AI scheduling recommendations. It clearly separates the tool from create_meeting_poll and submit_participant_vote, which are named as alternatives.

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 explicitly names both sibling tools and instructs not to use this tool when a more specialized one fits better. However, the positive 'when to use' clause is largely circular ('when you specifically need to execute get_poll_consensus'), so it does not give a concrete scenario beyond the purpose sentence.

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=false, destructiveHint=false, idempotentHint=false, and openWorldHint=true, but the description goes further by disclosing a backend write, no authentication for public initiation, and a 60 requests/min per-IP rate limit — meaningful context an agent cannot derive from the annotations. It does not address duplicate-vote behavior despite idempotentHint=false, which keeps it from a 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?

The core purpose is front-loaded, but the body is padded with self-referential filler ('Call this tool when you specifically need to execute submit_participant_vote') and a generic Returns paragraph describing 'status, matched records or computed metrics' that could belong to any tool in the server.

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 four-parameter mutation with no output schema, the description supplies a workable picture — write behavior, rate limit, auth posture, and a rough return shape. It falls short on the edge cases that matter for a non-idempotent vote tool: what happens on resubmission, whether out-of-range slot indices are rejected, and whether email matching deduplicates participants.

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%, so all four parameters and their required/optional status are already documented in the schema. The description only restates the same required/optional labels and adds no syntax, format, or semantic detail (e.g., how slot indices map to poll slots), so baseline 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 — submitting a participant's availability votes on candidate meeting slots — which is clear enough to distinguish it from the sibling tools. The clarity is undercut slightly by the boilerplate 'When to use' clause that merely restates the tool name, adding no differentiating detail.

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 does name the siblings (create_meeting_poll, get_poll_consensus) and says not to use this tool when another fits better, but it never states the actual condition that selects this tool or those alternatives, deferring to 'their respective operations.' That is implied routing rather than explicit guidance, and no preconditions (e.g., poll must exist, one vote per participant) are given.

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