personhood

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

With no annotations provided, the description carries the full burden. It states what is returned (spendable credit balance) but does not explicitly mention read-only behavior or potential error conditions. For a trivial non-mutating query, the behavior is largely implied by the name, but the description alone is minimal.

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, short phrase that is extremely concise and front-loaded. It contains no wasted words and conveys the essential information in minimal space.

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 balance query with no parameters and an output schema, the description sufficiently communicates the tool's purpose. It could have explicitly noted read-only behavior, but the overall simplicity makes this a minor gap rather than a critical omission.

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 description does not need to provide parameter semantics. The empty schema is fully covered, and the baseline for 0 params is 4. No additional parameter information is necessary.

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 'Your current spendable credit balance' clearly identifies the resource and its nature, and the tool name 'get_balance' reinforces it as a retrieval operation. It is unambiguous and distinct from sibling tools, though it lacks an explicit verb like 'returns' or 'fetches'.

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 provided on when to use this tool versus alternatives. The sibling tools are unrelated, and the description gives no context about prerequisites, exclusions, or typical use cases.

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 discloses important behaviors: blank persona_id is rejected before credit is spent, and platform mode tightens the opening hook. It also implies credit usage and dependency on list_personas. Missing details like rate limits and side effects are not disclosed, but the description goes beyond core purpose.

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 three concise sentences. The first states the core purpose, the second provides prerequisite and validation info, and the third covers an optional mode. 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 moderate-complexity tool with 4 parameters and an output schema, the description is largely complete. It covers the main behavior, prerequisites, and error handling, but misses the context parameter entirely. Overall, it provides sufficient guidance for an agent to select and invoke the tool.

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 explains text (rewritten), persona_id (required, blank rejected), and platform (optional 'linkedin' mode). The context parameter is left undocumented, which is a gap, but the other parameters are well explained.

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 rewrites text to sound human in a persona's voice, which is a specific verb+resource. This distinctly separates it from sibling tools like get_balance and list_personas.

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 clear usage context including a prerequisite (call list_personas first), required persona_id, and optional platform mode. However, it does not explicitly state when not to use or mention alternatives beyond list_personas.

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 that the tool returns a list of built-in and custom personas, providing some behavioral context. However, with no annotations, it does not explicitly state read-only nature, return format, or potential edge cases, leaving some burden unmet.

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, front-loaded sentence using a parenthetical for extra detail. Every word earns its place, with no redundancy or 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 zero-parameter listing tool with an output schema, the description adequately covers the essential purpose and content. It could mention ordering or use-case triggers, but those are not critical given the tool's 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 input schema has zero parameters, so there is nothing for the description to add. The baseline of 4 applies, and the description appropriately avoids stating anything about parameters.

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 uses a specific verb ('List') and resource ('personas'), and further clarifies scope with 'selectable' and 'built-ins plus your custom personas.' This distinguishes it from the sibling tools (get_balance, humanize) which serve entirely different purposes.

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 'List selectable personas' implies when to use the tool: when an agent needs to see available personas for selection. However, it does not explicitly state alternatives or exclusions, but given the sibling tools are unrelated, the context is sufficiently clear.

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