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

With no annotations, the description carries the burden of explaining behavior. It usefully discloses that only `call_tool(tool_name: str, params: dict) -> Any` is in scope and that output is produced with `return`. However, it does not describe execution environment constraints, error behavior, side effects, or persistence across blocks, leaving meaningful gaps.

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 short sentences with no filler. The core instruction is front-loaded, and every sentence contributes either to usage, output, or scope constraints.

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 single-parameter tool with no output schema, the description is largely sufficient: it explains how to invoke tools, how to return output, and what is available in scope. It could be more complete by noting error/exception behavior or execution restrictions, but these are not critical for basic usage.

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 already documents `code` at 100% coverage, but the description adds real value by specifying the callable signature, the need for `await`, and the output mechanism. This goes beyond merely restating the 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 clearly states that the tool executes a Python block which chains `await call_tool(...)` calls and returns output via `return`. It is not a tautology and gives a concrete sense of the tool's role, though it does not explicitly differentiate itself from siblings like `search` or `get_schema`.

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 gives clear context for when to use the tool: when multiple tool calls need to be chained in one Python block, and it advises preferring a single block and using `return`. It lacks explicit exclusion criteria or named alternatives, but the usage intent is clear.

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 burden of conveying behavioral context. It does present this as a read/inspection operation ('Get', 'Use after searching'), and the output schema partially covers return behavior. However, it does not explicitly state that the tool has no side effects, does not execute the requested tools, or how it behaves if a tool name is invalid.

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 short sentences with no filler. The main purpose is front-loaded, and the workflow guidance directly follows. Every sentence 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?

For a low-complexity introspection tool with an output schema and fully documented parameters, the description is largely sufficient. It gives the workflow context ('after searching') and the goal ('detail needed to call a tool'). The main missing piece is a brief note on side-effect-free behavior, but this is minor for a tool like this.

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 already provides 100% coverage with meaningful descriptions for both tools and detail, including the enum meanings. The description adds little parameter-specific value beyond the phrase 'detail needed to call a tool,' so the baseline 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 identifies the action ('Get') and resource ('parameter schemas for specific tools'), so an agent can quickly understand what the tool does. However, it slightly undersells the output: the detail parameter can return names/descriptions and full JSON schemas, not just parameter schemas. It also doesn't explicitly differentiate from execute, though the workflow hint helps.

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 to use this tool 'after searching' and frames it as the step to obtain 'the detail needed to call a tool.' This gives useful sequencing relative to the sibling tools search and execute. It stops short of naming explicit exclusions or when not to use it, so it is clear but not fully exhaustive.

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 must carry behavioral disclosure. It states that matching tools are returned ranked by relevance, which is a clear behavioral promise. It does not mention safety, side effects, or authentication, but for a read-only search tool the disclosed behavior is adequate.

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 concise sentences. The primary action is front-loaded, and the additional sentence about ranking is useful without unnecessary detail.

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 discovery tool with full schema coverage and an output schema, the description is largely complete. It could be enhanced with usage guidance or explicit differentiation from sibling tools, but nothing essential for invoking it correctly is missing.

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 four parameters. The description adds context about ranking but does not meaningfully elaborate on query, tags, limit, or detail beyond what the schema provides, matching the baseline.

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 searches for available tools by query and returns ranked results, so an agent understands the core action and resource. However, it does not explicitly differentiate this tool from siblings like get_schema or execute, relying on the tool name and context rather than the description.

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?

There is no guidance on when to use this tool versus alternatives. The description implies it is for discovering tools, but it does not state prerequisites, exclusions, or how it relates to get_schema or execute.

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