按机构名称关键词搜索投资机构，返回机构ID、案例数、最近投资时间和活跃行业。
| Name | Required | Description | Default |
|---|---|---|---|
| is_fa | No | ||
| cursor | No | ||
| fields | No | ||
| keyword | No | ||
| prop_ids | No | ||
| page_size | No | ||
| is_state_owned | No | ||
| is_government_guidance_fund | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | 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?
No annotations are provided, and the description does not disclose behavioral traits like pagination, rate limits, or side effects. It only mentions return fields, which adds minimal transparency.
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 concise sentence, but it could include more details without being verbose.
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 tool with 8 parameters and no schema descriptions, the description is incomplete. It does not explain the usage of most parameters.
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 has 8 parameters with 0% description coverage. The description only mentions the keyword parameter implicitly, ignoring other parameters like cursor, page_size, and fields.
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 clearly states the action (search by keyword) and resource (investment institutions), and lists returned fields. However, it does not differentiate from sibling tools like search_companies or search_investor_cases.
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 provides no guidance on when to use this tool versus alternatives, such as other search tools in the sibling list.
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 targets a distinct resource and action: counting vs searching vs retrieving profiles vs ranking vs resolving. There is no ambiguity as tools like count_companies and search_companies have clearly separated purposes (count vs list). Even similar tools like search_companies and search_closed_companies are distinguished by company status.
All tool names follow the verb_noun pattern (e.g., search_companies, get_company_profile, resolve_companies) using snake_case consistently. The naming is predictable and clear, with only minor variations like aggregate_funding_by_tags which still starts with a verb.
With 17 tools, the server covers a comprehensive set of operations for a company/funding database without being overwhelming. Each tool serves a specific need, and the count aligns well with the domain's complexity.
The tool set covers all major operations for querying companies, funding, investors, events, FA cases, tags, and lookups. It includes both aggregated counts and detailed listings, ranking, and name resolution. No obvious gaps for a read-only data retrieval server.
