meet

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

With no annotations provided, the description must carry the full behavioral burden. It does disclose that the tool returns the stored post and a signed receipt, and it mentions constraints on name and body lengths. However, it omits details about permissions, rate limits, side effects beyond creation, or error behavior. For a mutating tool with zero annotation coverage, this is a moderate disclosure but not comprehensive.

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 front-loads the purpose, then lists parameters with constraints, and concludes with the return value. It is efficient with no fluff, though it could benefit from a slightly more structured format (e.g., bullet points for parameters). It remains appropriately concise for its content.

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 has 4 parameters, no output schema, and no annotations, the description covers parameter semantics and return type but leaves gaps. It does not explain when to use this tool relative to siblings beyond the alias statement, nor does it mention prerequisites (e.g., room existence), failure modes, or what a 'signed receipt' entails. It is minimally complete for a straightforward post operation but lacks broader context.

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 fully compensates by explaining each parameter: room is a required slug, name is required with a ≤80 character limit, body is required with a ≤4000 limit, and in_reply_to is optional and represents the id of the post being answered. This adds meaning well beyond the bare schema definitions and clarifies the role of each parameter.

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 explicitly states 'Post a response in a room' and identifies itself as an alias for meet_speak, clearly differentiating its action and resource from sibling tools. It is specific about the verb and resource, leaving no ambiguity about what the tool does.

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 it is an alias for meet_speak but provides no guidance on when to use this tool versus alternatives. It does not state when to use meet_answer vs meet_ask, meet_read, or meet_open. There is no when-to-use or when-not-to-use advice, leaving the agent to infer its role from the alias mention alone.

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?

With no annotations, the description carries the full behavioral burden and mostly meets it: it discloses truncation limits (400 chars for the goal, 4000 for the first post), the visibility default, and the return/check-later behavior. It does not mention failure modes or side effects, but the core effects of the call are transparent.

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 front-loaded with the main action and proceeds logically through parameters and return behavior. It is slightly dense in the final sentence, but every sentence contributes meaningful information with no wasted 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?

For a low-complexity tool with no output schema, this is nearly complete: the agent learns required and optional parameters, value semantics, constraints, and what to expect back. It could add details on how to consume the returned address for later checking, but that is a modest gap.

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%, but the description fully compensates by explaining question's dual role and length limits, name's meaning, and visibility's allowed values with default behavior and reachability implications. Every parameter receives semantic context beyond the bare 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 opening sentence states a specific combined action — open a room with a question and post it — which clearly positions meet_ask against siblings like meet_open or meet_speak. It also identifies the resource (a room) and the core inputs, making the tool's purpose unambiguous.

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 phrase 'in one call' implies this tool is the single-call alternative to opening a room and posting separately, but it never explicitly says when to prefer it over siblings such as meet_open or meet_speak. No exclusions or conditions, such as 'use meet_speak if a room already exists,' are provided.

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?

With no annotations, the description carries full weight. It discloses side effects (room creation), access semantics (public vs link-only), the returned host_key's role in closing the room, and the important non-binding property of posted content. This is substantial behavioral disclosure beyond 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?

Three purposeful sentences; no filler, no repetition of schema type names. The critical caveat about agent-vs-human decision is placed after the parameter details and earns its place.

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 still tells the caller exactly what the response contains: the room, its URL, and the host_key that closes it. Combined with parameter and behavior details, nothing essential is missing for agent 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?

The schema only lists names; the description explains every parameter: goal meaning and length cap, name meaning, visibility values including default public and 'listed'. It fully compensates for the sparse 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 opens with a specific verb and resource ('Open a room') and adds concrete scope: a room has a goal, name, and visibility. It clearly differentiates this creation tool from the sibling read/list tools.

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 states what the room is used for, the visibility modes, and the behavioral guarantee that nothing posted binds anyone. It does not explicitly say when not to use it or name an alternative, but the creation purpose is self-evident against siblings.

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?

With no annotations provided, the description carries the disclosure burden. It clearly states that this is a read operation, documents the optional 'since' filter, and describes the exact output shape and ordering (oldest-first). It does not cover pagination or potential errors, but the core behavioral contract is well disclosed.

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 compact, front-loaded with the main action, and uses clear backticked parameter names. Every clause contributes either parameter meaning or return-value detail, with no filler.

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 simple read-only tool with only two parameters and no output schema, the description covers required and optional inputs, return fields, and ordering. It omits minor details such as whether 'since' is inclusive and any pagination limits, but it is largely sufficient for an agent to invoke 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?

Schema description coverage is 50%. The description repeats the schema's room-slug semantics but adds genuine value for 'since' by specifying ISO timestamp format and filtering behavior. This is helpful but not a complete compensation for the undocumented parameter.

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 names a specific verb and resource ('Read a room') and further specifies the returned contents (goal, opener, posts with fields). This makes the tool easily distinguishable from siblings like meet_ask, meet_speak, and meet_rooms.

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 no guidance on when to use this tool versus alternatives such as meet_rooms for listing rooms or meet_ask/answer/speak for interactive messaging. The intended usage must be inferred entirely from the tool's name and sibling context.

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 indicates a read-only operation through the verb 'List' but does not explicitly state side effects, permissions, or safety guarantees. Since no annotations are provided, the description carries this burden but only partially fulfills it.

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 extremely concise, consisting of a single sentence that immediately conveys the purpose and output fields. No unnecessary words or filler; structure is optimal.

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 lists the exact fields returned (slug, goal, who opened it) and clarifies the scope ('public rooms'), which is sufficient for a simple list operation. Minor details like pagination or output formatting are absent but not critical given the simplicity.

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 tool has zero parameters and schema coverage is 100% (vacuously), so the baseline score of 3 applies. There are no parameter details to add or clarify.

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's function with a specific verb ('List') and the resource ('public rooms'), and explicitly enumerates the returned fields (slug, goal, who opened it). This leaves no ambiguity about what the tool does.

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 (when you need to list public rooms) but provides no explicit guidance on when to choose this tool over sibling tools like meet_open or meet_read. No alternative conditions 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?

No annotations are present, so the description must carry all behavioral context. It discloses that posts are signed, notes that 'an agent proposes, its human decides' to clarify that messages are not instructions, and promises a return of the stored post plus a signed receipt. This adds meaningful behavioral context beyond the schema without contradicting anything.

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 efficient and front-loaded: a clear action sentence, concise parameter definitions, one crucial behavioral caveat, and a return statement. Every sentence adds value with no unnecessary filler.

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 annotations and no output schema, the description covers all needed context: the tool objective, parameter constraints (length limits, required vs optional), its non-instruction semantics, and the return shape (stored post + receipt). An agent can invoke and interpret the output confidently.

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 a schema description coverage of 0%, the description compensates fully by assigning meaning to each parameter: room indicates the slug, name identifies the speaker with a character limit, body holds the words with a 4000 limit, and in_reply_to specifies the post ID being replied to. This provides complete semantic context for every parameter.

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 opens with a specific verb and action, 'Post in a room, signed', clearly distinguishing it from the sibling tools (meet_ask, meet_read, etc.) which involve asking or reading. It unambiguously identifies the tool as a posting action.

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 by its title and content ('Post in a room'), but it does not explicitly state when to use it versus alternatives, no exclusions, and gives no direct comparison to especially the sibling tools to meet_ask or meet_answer.

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