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

With no annotations, the description carries the full burden. It discloses the return payload ('title, url, text, and truncated/stale flags') and implies a read-only operation via 'Fetch.' It also mentions 'truncated/stale flags' which is a useful behavioral nuance. However, it lacks explicit statements about side effects (or lack thereof), error handling, or prerequisites beyond the search step.

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 sentences, front-loaded with the core purpose, and includes only essential information. Every sentence adds value—first the action, then the usage pattern, then the return summary. 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?

The tool is simple, has an output schema (though not shown in the prompt), and the description covers the return structure. The navigation hint from search is a useful context. The only gap is the undocumented 'version' parameter and lack of explicit error or timeout behavior, but these are not critical for a simple fetch 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?

The schema has no parameter descriptions (0% coverage), so the description must clarify. It clarifies 'url_or_href' by tying it to the search output, but it doesn't explain 'version' at all, leaving that parameter ambiguous. The parameter names themselves are somewhat self-explanatory, but the description only partially compensates for the gap.

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 begins with 'Fetch one IBM i documentation topic as plain text,' which clearly identifies the action (fetch), the resource (IBM i documentation topic), and the output format (plain text). This distinguishes it from the sibling tool 'search_ibm_docs' by focusing on retrieval of a specific topic 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?

The description explicitly instructs to 'Pass the href (or content API URL) from search_ibm_docs' and advises to 'Prefer search first so you pick the right page.' This provides clear when-to-use guidance and names the alternative workflow, leaving no ambiguity about ordering.

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 carries the transparency burden. It discloses two key behaviors: results are ranked by IBM relevance, and the top hit may not be correct, advising to 'read titles/snippets.' It also reveals the output includes hrefs for the next step. This is significant added context beyond the schema.

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, front-loaded with the core purpose, followed by actionable usage tips. Every sentence adds value: the first states what it does, the second covers query style, ranking behavior, and the next step. No fluff or 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?

The description covers the essential search workflow, including result ranking caveat and the follow-up fetch step. With an output schema present, the description doesn't need to detail return structure. However, the lack of parameter definitions for limit/version slightly reduces completeness for a tool with three parameters.

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 only addresses the query parameter by recommending short names, but offers no explanation for 'limit' or 'version'. Although their defaults are in the schema, their meaning and usage are not clarified, leaving a clear gap.

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 'Search IBM i documentation (IBM's own docs search index)', specifying the exact verb and resource. It also distinguishes the tool from its sibling by stating the next step to call fetch_ibm_doc, making the search vs. fetch difference explicit.

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 gives clear guidance on how to use the tool: 'Prefer short object/command names' and 'call fetch_ibm_doc with the chosen result's href.' This establishes the workflow and query strategy, though it doesn't explicitly state when not to use it or enumerate exclusions.

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