fetchFull catalog card for one expert by id (their slug), including the MCP connector URL your agent connects to consult them. Read-only.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | An id returned by search. |
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| url | Yes | ||
| text | Yes | ||
| title | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent, and non-destructive behavior; the description adds useful context that the returned catalog card includes the MCP connector URL, and clarifies that the id is actually the expert's slug. No contradiction with annotations.
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 sentence that front-loads the core purpose, specifies the key output feature, and notes read-only behavior. Every phrase earns its place with no fluff or repetition of obvious schema details.
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 single-parameter, read-only fetch tool with an output schema and strong annotations, the description provides all necessary semantics: what the tool returns, what the id means, and the special connector URL. Nothing essential is missing.
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 already documents the single required parameter, so the baseline is high. The description adds meaningful nuance by explaining that 'id' is the expert's slug, and the schema's note that it comes from search complements that. Coverage is 100%, and the description strengthens the meaning beyond the raw 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 states a clear verb, 'Full catalog card for one expert by id', and distinguishes the tool from the sibling 'search' by focusing on a single record retrieved by identifier. The added detail about including the MCP connector URL gives a precise, non-redundant purpose.
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 tool is for retrieving a single expert once its id/slug is known, but it never explicitly says 'use this when you have an id from search' or contrasts it with the sibling 'search'. The usage is clear enough by context, but exclusions or alternative-selection guidance are absent.
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.
fetch and search have clearly distinct roles: one locates expert IDs by query and the other retrieves a single full card by ID. There is no overlap or ambiguity between them.
Both tool names are single lowercase verbs describing the core action, making the naming simple and predictable. The pattern is consistent across the small surface.
Only two tools is slightly below the typical 3-15 range, but for a read-only catalog the search-then-fetch pair is tightly scoped and neither tool feels redundant.
For this read-only catalog, the surface is complete: search covers discovery and fetch covers retrieval of the full expert record. There are no obvious dead ends or missing lifecycle operations.