Return the full text behind a search result. Pass a doc slug ("help/columns/column-definitions") or a demo id prefixed with "demo:" ("demo:11-stock-market").
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | A doc slug, or "demo:<id>". |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It does communicate the core behavior: returning full text for a given slug or demo id. But it does not disclose response format, error behavior, or any non-obvious limitations, leaving meaningful gaps for an agent invoking the tool.
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 with the purpose front-loaded and no filler. The examples are tightly packed and directly support 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 one-parameter, no-output-schema tool, the description covers the necessary invocation details: what the tool does and exactly what forms the id can take. It does not explain the relationship to the search tool or address potential edge cases, but nothing critical appears missing for a tool this simple.
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 baseline is 3. The description adds concrete examples ('help/columns/column-definitions' and 'demo:11-stock-market') and reinforces the two accepted formats, but this is a modest addition beyond what the parameter description already states.
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 names a specific verb ('Return') and resource ('full text behind a search result'), and gives concrete examples of the two accepted input forms. It does not explicitly contrast itself with sibling tools such as get_example_source or check_svgrid_code, so it stops just short of full sibling differentiation.
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 phrase 'behind a search result' implies that this tool is for retrieving full content for items surfaced by search, and the id formats are clearly explained. However, it never explicitly states when to prefer this tool over alternatives or when not to use it, so usage guidance is only implied rather than stated.
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.
The search→fetch and list_examples→get_example_source pairs form clear workflows, and check_svgrid_code is distinct. The only real ambiguity is that fetch also accepts a demo id, which overlaps somewhat with get_example_source, though fetch returns page text rather than .svelte source.
Most tools follow a descriptive verb_noun pattern: get_api_reference, get_example_source, list_examples, check_svgrid_code. The bare verbs search and fetch are minor deviations, but the names remain predictable and easy to distinguish.
Six tools is a tight, well-scoped set for a documentation-and-code-support server. Each tool earns its place and together they cover discover, read, reference, example, and verify workflows without redundancy.
The tool surface covers the full assistant loop: search documentation, fetch doc content, read the API reference, browse and copy demo source, and validate code against the real SvGrid API. There is no obvious missing operation that would create a dead end for an agent.