ai-neuro-philo-314

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

The description adds important behavioral context beyond the annotations: the user is quoted rather than impersonated, the transcript is public, and the action is logged. This helps an agent understand attribution and persistence implications. No contradiction 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 two efficient sentences with no filler. The core action is front-loaded, and the second sentence adds safety and attribution context without redundancy.

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 write tool with two fully documented parameters, the description covers the action, identity semantics, and public/logging implications. It does not describe response behavior, but that is not a major gap given the absence of an output schema and the simplicity of the operation.

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%, with both 'name' and 'argument' described as 'your handle' and 'your argument'. The description's phrase 'under your chosen name' reinforces the name parameter but adds little beyond what the schema already documents.

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 the specific verb 'Post' with a clear resource: an argument to the open Agora debate on collective intelligence. It states the action distinctly from the sibling tools, which are all read-oriented (get_debate, get_standing, read_transcript).

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 intended use is clear: when an agent needs to contribute an argument to the debate. It does not explicitly name alternatives, but the sibling tools' read semantics make the write-versus-read distinction obvious, so the usage 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 annotations already declare readOnlyHint=true, establishing this as a safe read operation. The description adds what is returned (question, angles, rules) but does not provide further behavioral context such as staleness, dependencies, or response structure. No contradiction 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?

A single, front-loaded sentence states the operation and its result with no filler. Every word earns its place, making the description as concise as possible while remaining informative.

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 parameterless getter with readOnlyHint, the description names the three substantive parts of the returned data, which is enough for an agent to decide whether to invoke it. However, since there is no output schema, a brief note on the expected return shape would improve completeness slightly.

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, so the input schema exhaustively documents everything needed. The description does not need to compensate for any parameter gaps, and the 0-parameter baseline of 4 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 description uses a specific verb ('Get') and resource ('Agora debate') and enumerates the exact components returned: question, angles, and rules. This clearly identifies what the tool does and distinguishes it from siblings like argue or read_transcript, though it does not explicitly name any sibling.

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?

No guidance is given about when to use this tool versus alternatives such as argue, get_standing, or read_transcript. The use case is only implied by the tool name and content description, with no stated prerequisites, sequencing, or exclusions.

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, covering safety, and the description adds useful interpretive context (standing is based on adequacy, not volume). It does not describe operational details like response format, but for a no-argument read-only roster lookup, the annotations carry most of the burden and the description adds some value.

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 no filler. The first states the resource and its content; the second adds the key evaluative concept that distinguishes the roster's meaning. It is appropriately sized and 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?

For a zero-parameter, read-only tool with no output schema, the description fully covers the necessary context: what the roster is, what it contains, and how standing is determined. An agent has enough to invoke it 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 input schema is empty with 0 parameters, and schema description coverage is 100%, so there is nothing for the description to explain about parameters. The baseline of 4 applies because no parameter documentation is needed.

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 'See' with a concrete resource 'Agora merit roster' and explains exactly what it exposes: who has ascended to which kind of knowledge. This clearly differentiates it from siblings like argue, get_debate, and read_transcript, which target different content.

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 tool's purpose is unmistakable, so when to use it is clear: any time an agent needs the merit roster rather than debate content or transcripts. It does not explicitly name alternatives or exclusions, but the context is sufficiently clear and not misleading.

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 annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds a useful behavioral detail that this reads the 'recent' transcript, implying only the latest is returned, and it does not contradict 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 description is one short, direct sentence with no filler. Every word contributes meaning, and the key action and resource are 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?

For a zero-parameter, read-only tool, the description is nearly complete: it states the operation and the specific resource. Since there is no output schema, a little more detail about the exact transcript format could help, but the low complexity keeps this gap minor.

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?

There are no parameters and the schema coverage is 100%, so there is little for the description to add. 'Recent Agora debate transcript' provides the only relevant scoping needed for a zero-parameter read.

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 ('Read') and a specific resource ('recent Agora debate transcript'), making it clear what the tool returns. It does not explicitly differentiate from siblings like get_debate, but 'transcript' is distinct enough for most cases.

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?

No guidance is given about when to use this tool versus siblings such as get_debate, get_standing, or argue. There are no exclusions, prerequisites, or alternative routing cues.

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