Read one full Atisbo documentation page as markdown, by its site-relative URL (for example /docs/api/webhooks).
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Site-relative URL of the page, as returned by search_docs or list_docs. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already establish the read-only, non-destructive nature, so the description doesn't need to repeat that. It adds useful behavioral detail by stating the whole page is returned as Markdown and that the input is a site-relative URL, which clarifies exactly what the tool does beyond a simple read hint.
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 one compact, front-loaded sentence that includes the key action, resource, return format, and an example. No filler words; every element contributes to correct invocation.
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 read-only tool with a clear output format and sibling tools referenced by the schema, the description is fully sufficient. No output schema is needed because the description states the return format as Markdown, and the annotations already signal safety.
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 baseline is 3. The description adds value beyond the schema by providing a concrete example URL ('/docs/api/webhooks') and restating the site-relative-URL requirement in context, helping an agent correctly format the single parameter.
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?
Uses a specific verb ('Read') and resource ('Atisbo documentation page'), and uniquely identifies the addressing scheme (site-relative URL) and return format (markdown). This clearly differentiates it from sibling tools list_docs and search_docs, which return collections or search results.
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 implies the intended flow: use search_docs or list_docs to obtain a site-relative URL, then call get_doc with that URL. The schema reinforces this by stating the URL is 'as returned by search_docs or list_docs.' It does not explicitly list exclusions, but the usage context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clear, non-overlapping purpose: get_doc retrieves a single page, list_docs enumerates available pages, and search_docs finds pages by query. There is no ambiguity about which tool to use in a given situation.
All three tools follow a uniform verb_noun snake_case pattern: get_doc, list_docs, search_docs. This makes the toolset predictable and easy to learn.
Three tools is well-scoped for a read-only documentation server. Each tool covers a distinct and necessary operation without redundancy or bloat.
The toolset fully covers the documentation browsing workflow: discover pages (list_docs), find relevant content (search_docs), and read specific content (get_doc). No create/update/delete is expected for a documentation corpus, so there are no meaningful gaps.