Search a knowledge graph for entities by query, with optional type and pool filters, to locate relevant people, concepts, or records.
Search for entities in the knowledge graph.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Entity search query | |
| top_k | No | Max results (default: 20, max: 100) | |
| pool_name | No | Pool name | |
| entity_type | No | Filter by type (person, concept, etc.) |
Changes observed during successful MCP inspections.
v2.4.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden, but it discloses almost nothing. It does not state that this is a read-only operation, how results are ranked or paginated, what the default pool behavior is, or what the response contains.
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 front-loaded sentence with no wasted words. However, its brevity reflects under-specification rather than efficient communication, since it omits information an agent needs to select and invoke the tool correctly.
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?
With no annotations, no output schema, four parameters, and dozens of sibling search tools, the one-sentence description is not complete enough. It leaves the agent unable to confidently distinguish this tool from related search tools or understand its operational behavior.
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 query, top_k, pool_name, and entity_type are already documented in the schema. The description adds no extra meaning about how these parameters interact or what entity_type values are valid beyond the schema's examples.
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 and resource: searching for entities in the knowledge graph. It is clear what the tool does, but it does not distinguish this from the many sibling search tools such as trawl_search, trawl_search_multi, trawl_search_relationships, or trawl_find_symbol.
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 guidance on when to use this tool versus alternatives, no prerequisite or scope information, and no exclusions. The agent is left to infer usage from the name alone despite a crowded set of sibling search tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.