UmbHost Knowledgebase

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

No annotations are supplied, so the description carries the burden. It usefully discloses the return format ('full markdown'), which tells the agent what it will get back, but says nothing about permission requirements, truncation/pagination on large pages, or error behavior for a bad path.

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?

One sentence, front-loaded with the action and resource, with the qualifier about path provenance trailing. Nothing is wasted and nothing essential is missing.

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 one-parameter read tool with no output schema, the description covers what it does, what it takes, and what it returns (full markdown). The only shortfall is the absence of any note on failure modes or size limits, which is minor for this complexity.

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% and the single 'path' parameter is documented in the schema as 'The doc path or URL'. The description reinforces the provenance of the value (from search_docs/list_docs) but adds no syntax or format detail beyond the schema, so baseline 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?

States a specific verb (Fetch), a specific resource (one documentation page), and a specific return format (full markdown) keyed on the path. The 'one page' scoping implicitly separates it from the list_docs/search_docs siblings, though it never names them as alternatives.

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?

Gives clear context for when to use it and where the argument comes from ('as returned by search_docs or list_docs'), establishing the retrieve-after-search workflow. It stops short of stating exclusions or what to do when the path is unknown.

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?

No annotations are provided, so the description carries the full behavioral burden. It discloses the shape of the result (title, description, URL), which is useful, but says nothing about volume, pagination, ordering, permissions, or whether the whole corpus is returned unbounded.

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 front-loaded sentence that states the action, the scope ("every"), and the payload, with no filler. Every clause 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 zero-parameter list tool with no output schema, the description is nearly sufficient: it names the returned fields, which partly substitutes for a missing output schema. It falls short only on volume/pagination behavior, which matters for an unfiltered "every page" listing.

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 takes zero parameters, so per the baseline there is nothing for the description to disambiguate. It does not need to compensate for any schema 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 uses a specific verb+resource ("List every documentation page") and even names the fields returned (title, description, URL), so the purpose is unambiguous. However, it never contrasts itself with the siblings get_doc and search_docs, leaving the agent to infer the boundary between listing, fetching one, and 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?

There is no explicit when-to-use guidance, no exclusions, and no mention of the sibling tools. The word "every" weakly implies enumeration as opposed to search or single-fetch, but the agent is left to infer that from the sibling names alone.

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 full behavioral burden. It usefully discloses that results are ranked best matches with snippets and URLs, but it does not address read-only safety, authentication, rate limits, or pagination behavior.

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?

Two concise sentences with the core purpose and return format front-loaded. Every sentence contributes useful information 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 simple one-parameter search tool with 100% schema coverage and no output schema, the description covers purpose and return values adequately. The main missing element is routing guidance relative to sibling tools.

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 single query parameter is fully documented in the schema as "What to search for," so the description does not need to compensate. It adds no additional syntax or formatting detail beyond 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 gives a specific verb and resource ("Search the UmbHost Knowledgebase documentation") and states the return shape (best-matching pages with snippets and URLs). It is clear what the tool does, but it does not explicitly differentiate it from siblings like get_doc or list_docs.

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 explicit guidance on when to use search_docs versus get_doc or list_docs. The description implies keyword-based retrieval but leaves the choice between tools to inference.

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