list_technologiesCatalog of all technologies in the dataset with per-technology company counts. sort='count' (most used first) or 'name'.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| sort | No | count | |
| page_size | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly and idempotent behavior. The description adds transparency about sorting behavior and output structure (company counts), which goes beyond annotations.
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 extremely concise with no extraneous words. It gets straight to the point and fits in a single sentence.
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?
While the description covers the core purpose and sorting, it omits pagination behavior and does not fully describe the output format. Given the schema provides parameter details, some gaps remain.
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 description explains the 'sort' parameter's enum values but does not cover 'page' or 'page_size'. With 0% schema description coverage, partial compensation is provided.
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 tool lists all technologies in the dataset and provides per-technology company counts. It distinguishes itself from sibling tools that focus on companies rather than technologies.
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 usage for browsing technologies but does not explicitly state when to use this tool versus alternatives. No exclusions or when-not guidance are provided.
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 clearly distinct purpose: resolving a specific company, listing all technologies, or searching companies by technologies. There is no overlap or ambiguity.
All tool names follow a consistent verb_noun pattern in snake_case (get_company_by_domain, list_technologies, search_companies_by_technologies), making them predictable and easy to understand.
With 3 tools, the server is appropriately scoped for its purpose of providing technographic data. Each tool is essential and covers the primary operations needed.
The tool surface covers all obvious needs: retrieving company profiles, exploring the technology catalog, and searching for companies using specific technologies. There are no apparent gaps for a read-only technographics server.