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

The annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds no further behavioral context, such as that this invokes an external AI model or the nature of the plan output. It is not misleading, but it provides minimal additional transparency 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 description is a single sentence, front-loaded with the usage condition and action. It is concise and easy to parse. However, it is also under-specified, lacking useful context about the planning process, but it avoids verbosity.

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 tool has a rich schema and an output schema, but the description is very sparse. It does not explain what kind of project plan is produced or how the parameters are used. Given the richness of the structured fields, the description is minimally acceptable but could do more to aid selection.

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 has 100% description coverage for all 4 parameters, so the structured fields fully document them. The description does not add any parameter-specific semantics, relying entirely on the schema. Baseline 3 is appropriate since the schema carries the information.

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 states the action 'ask Kimi K3 to create a project plan' and the title says 'Plan a project', clearly indicating the tool's purpose. It is distinct from sibling tools 'review_algorithm' and 'review_code', which are for code review. However, the description is conditional and does not add detail beyond the title.

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 says 'Only when explicitly requested', providing a clear when-to-use condition and implying not to use it proactively. It does not name alternatives, but the siblings are clearly review tools, so there is no ambiguity. This meets the 'when' criterion but lacks explicit when-not and alternative references.

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 destructiveHint=false, covering the safety profile. The description adds the conditional trigger ('only when explicitly requested') but does not disclose further behavioral details such as external calls, latency, or result handling. This is acceptable given annotation coverage but not generous.

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 sentence that front-loads the key constraint and action. There is no wasted text, and the essential usage condition is immediately visible.

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 is brief, but the rich schema and annotations cover parameters and safety, and an output schema exists so return values are documented elsewhere. The main missing element is explicit connection to sibling tools, but the core trigger and action are sufficient for a simple review 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 100%: all four parameters have meaningful descriptions in the schema (algorithm, requirements, focus, context). The tool description itself adds no parameter-specific semantics, so the schema carries the full burden and the baseline score of 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 description clearly states the specific action 'challenge' applied to 'an algorithm' and names the target 'Kimi K3'. This distinguishes it from sibling tools like review_code and plan_project, which target different resources.

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 'Only when explicitly requested' provides a clear condition for invocation, effectively excluding proactive use. However, it does not explicitly mention alternatives or contrast with sibling tools, so it stops short of a 5.

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 valuable behavioral context beyond the annotations: it requires an explicit request and reveals that the tool delegates to an external AI (Kimi K3). The annotations already provide readOnlyHint=true and destructiveHint=false, so the safety profile is well covered, and the description is consistent with them.

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 that states the key usage condition and the core purpose. There is no filler or 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?

The description, combined with complete schema coverage, output schema, and annotations, provides enough information to invoke the tool correctly. It could mention alternative tools or process details, but the essential rule (explicit request) is covered.

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?

All four parameters have descriptive schema entries (100% coverage), so the schema handles parameter semantics. The description itself adds no additional parameter-level detail, warranting the baseline score of 3.

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 identifies the action ('review code or a diff') and the resource (code/diff with Kimi K3), making the purpose specific. It does not explicitly differentiate from sibling tools like review_algorithm, but the name and target resource provide enough distinction.

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?

'Only when explicitly requested' is a strong, explicit usage condition, telling the agent not to invoke this tool proactively. It doesn't mention alternative tools or exclusions, but this condition alone gives clear guidance on when to use it.

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