search
Free-text search across all entity types (companies, markets, assets, funds, banks, countries, research). Returns grouped matches with links.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
Free-text search across all entity types (companies, markets, assets, funds, banks, countries, research). Returns grouped matches with links.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. It does state that results are 'grouped matches with links,' which adds useful output-format context, but it does not mention behavior limits, ranking, pagination, result count, or any read-only guarantees. Some behavior is disclosed, but not comprehensively.
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 compact and front-loaded: the first sentence establishes the operation and scope, and the second states the return format. Every word earns its place, with no filler or redundant restatement of the tool name.
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 tool with no output schema and no annotations, the description covers the core operation and the general return shape. However, it lacks guidance on result boundaries, how matches are grouped, and how this differs from nearby tools like lookup or graph, leaving an agent with incomplete context for confident invocation.
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 0%, so the description must compensate for the undocumented 'query' parameter. It says this is a free-text search, which clarifies that query is a natural-language search string, but it adds no format constraints, length guidance, or examples. The description provides minimal but non-trivial semantic value beyond the bare 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 names a specific verb ('Free-text search') and a clear resource scope ('all entity types') with concrete examples, making the purpose easy to grasp. However, it does not explicitly differentiate itself from sibling tools like lookup or resolve_identifier, aside from the implied breadth of 'all entity types.'
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 this is the tool to use for broad, free-text searching across multiple entity types, but it does not state when to prefer it over lookup, resolve_identifier, or list. No explicit exclusions or alternative routing are provided, so the agent must infer usage from the wording.
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 distinct retrieval mode: search/list for discovery, lookup/resolve_identifier for exact entity access, graph for relationships, live_data for reference values, and ingest_text for text extraction. Despite several retrieval tools, their input/output contracts are clearly separated in the descriptions.
Names are mostly lowercase and readable, but they mix single-word commands (graph, list, lookup, search), noun phrases (live_data), and verb_noun compounds (ingest_text, resolve_identifier). There is no consistent verb_noun pattern, so the set feels slightly ad hoc.
Seven tools cover the server's read-only knowledge-base scope without bloat: each operation (discover, resolve, look up, traverse, get live data, ingest text) maps to exactly one tool. This is well within the ideal 3–15 range.
The surface covers the main entity lifecycle: search/list to find, lookup/resolve_identifier to retrieve, graph to expand relationships, live_data for current values, and ingest_text for parsing text. Minor gaps such as schema introspection or historical time-series would require workarounds, but core workflows have no dead ends.