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

Annotations already include openWorldHint and readOnlyHint. The description adds meaningful behavioral context: it warns that absence may reflect a connector gap rather than the law, and states that every gap carries a fallback. It also discloses return details like an as-of note and a non-empty gap list, going beyond the annotation metadata.

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 and front-loaded, starting with the core purpose, then giving a clear usage trigger, and ending with a Returns summary. Every sentence serves a distinct purpose 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 no-parameter tool with rich annotations and an output schema, the description fully covers when to use it, what it returns, and how to interpret results. It also explains fallback behavior, making it complete for an agent to decide when and how to invoke it.

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?

This tool has zero parameters and an empty input schema, so there is nothing to document. The baseline of 4 applies because parameter documentation is inherently complete; no additional explanation 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 opens with 'Declare what this connector covers, how it is sourced, and what it does NOT cover' — a specific verb and resource that clearly distinguishes it from search/get tools. It also emphasizes the gap-reporting nature, which is a distinct purpose from querying norms.

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?

Explicitly instructs when to call: before telling a user that the law does not contain something, and whenever a search comes back empty. This gives a concrete trigger and even explains why it should precede negative claims. The context of sibling tools further reinforces appropriate usage.

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, destructiveHint=false, etc. The description adds 'Fetch full detail' which is consistent but does not provide additional behavioral information such as error handling, rate limits, or authentication needs. With annotations covering the safety profile, the description adds minimal extra transparency.

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, concise sentence that immediately conveys the tool's purpose. It is front-loaded with the key action and resource, 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?

With one parameter, clear annotations, and an output schema (as indicated by context), the description is adequate. It could be enhanced by noting the output schema covers the full detail, but it is not necessary. The description is complete for this simple 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%, so the schema already documents the parameter. The tool description mentions 'by its BCN resource URI' which mirrors the schema's description. No new semantic information is added beyond what the schema provides. Baseline of 3 is appropriate.

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?

Description clearly states it fetches full detail of one Chilean norm by its BCN resource URI. The verb is specific, and the distinction from sibling tool 'cl_search_norms' is implied by focusing on a single norm by URI rather than searching.

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?

Usage is implied: use this when you have a specific URI. However, no explicit guidance is given about when not to use it or when to prefer the sibling tool 'cl_search_norms'. The description lacks explicit when/when-not alternatives.

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 indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which convey safety and idempotency. However, the description does not add any behavioral details beyond 'full-text search', such as pagination, rate limits, or search scope. Minimal added 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?

The description is a single sentence of five words, with zero waste. It is front-loaded with the key verb 'search', making the purpose immediately clear. Every word 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?

Given the tool's simplicity, good annotations, and presence of an output schema, the description is largely complete. It clearly specifies the resource (Chilean legislation titles) and operation (full-text search). Minor missing details like search behavior for special characters or case sensitivity are not critical for a basic search 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%, so the input schema already documents both parameters (query and limit) with descriptions. The tool description does not provide any additional semantic information beyond what is in the schema, meeting 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 verb 'search' and the resource 'Chilean legislation titles', making the tool's purpose immediately obvious. It distinguishes itself from the sibling tool cl_get_norm, which presumably retrieves a specific norm.

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 implicitly guides usage: use this tool for full-text search over titles, not for retrieving specific norms. The sibling tool cl_get_norm provides an alternative, and the context signals give enough information to infer when to use each.

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