批量把用户给出的公司简称或工商全称解析为 IT桔子 company_id，返回每个输入名称的候选匹配；工商名称、工商注册名称、工商全称对应字段 registered_name。适合处理用户给定的一批公司名单，例如先解析19家独角兽公司，再调用 get_company_funding_events 查询融资历史。
| Name | Required | Description | Default |
|---|---|---|---|
| names | Yes | ||
| fields | No | ||
| exact_only | No | ||
| limit_per_name | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry full burden. It states it returns candidate matches per input name and maps registered_name field, but lacks detail on error handling, fuzzy matching, concurrency, or required permissions. It does not contradict anything.
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 two sentences long, starting with the core functionality and following with usage guidance and an example. Every sentence adds value; no redundancy.
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?
The description covers the main use case and usage scenario adequately. However, it lacks details about optional parameters and edge cases. Given the existence of an output schema, the agent can understand return values, but param explanation is incomplete.
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 0%. The description explains that 'names' are company abbreviations or full registered names and mentions the 'registered_name' field, but does not clarify the meaning of 'fields', 'exact_only', or 'limit_per_name'. Partial coverage of parameters.
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 that the tool resolves company abbreviations or full registered names into IT桔子 company_id, returning candidate matches. It distinguishes itself from sibling tools like search_companies and get_company_profile by specifying it is a batch resolution tool for name-to-ID mapping.
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 explicitly says it is suitable for processing a batch of company names and provides a concrete example: first resolve 19 unicorn companies, then use get_company_funding_events. This tells agents exactly when to use it and suggests a next step.
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.
