searchFind published experts by domain, decision types, or wording. Returns result ids for fetch. Read-only.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | What kind of judgment you are looking for. |
| Name | Required | Description | Default |
|---|---|---|---|
| results | 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 declare readOnlyHint, idempotentHint, and destructiveHint. The description adds the important behavioral detail that the tool returns result ids (not full entity details), which shapes caller expectations. It restates 'Read-only,' matching the annotations without contradiction.
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 three concise sentences with no filler. The 'Read-only.' fragment duplicates the annotation, a minor redundancy, but the rest is tightly packed and front-loaded with the core purpose.
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 single-parameter search tool with an output schema, the description covers the purpose, query semantics, and the relationship to the fetch sibling. It does not detail result limits or pagination, but those are less critical given the simplicity and the presence of an output schema.
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 for the single 'query' parameter is 100%, but the description enriches it by specifying the kinds of accepted queries: domain, decision types, or wording. This gives the agent better guidance on what to put in the query than the schema's generic description alone.
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 clear verb and resource: 'Find published experts' in the Avva expert catalog. It also distinguishes the tool from its sibling by stating it returns result ids for fetch, making the tool's scope unmistakable.
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 workflow: search to find result ids, then fetch to retrieve full details. While it does not explicitly say 'use this when you need to locate experts' or exclude fetch, the phrase 'Returns result ids for fetch' provides clear contextual guidance.
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.