Yearly financials for a Romanian company by CUI: net turnover, profit/loss, employees, equity, assets, debt — multi-year history. 20 credits (charged only if data exists).
| Name | Required | Description | Default |
|---|---|---|---|
| an | No | Specific year (optional) | |
| cui | Yes | CUI digits | |
| api_key | Yes | Your DACIX API key (dacix_sk_...). Get one with store_register. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses the data returned (net turnover, profit/loss, etc.) and cost (20 credits, charged only if data exists). However, it does not mention authentication requirements (api_key) or rate limits, though these are standard.
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, front-loaded with the core purpose and data fields, followed by cost info. Every sentence adds value with no fluff.
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?
Given no output schema, the description partially explains returns (multi-year history of specific fields) but does not describe format (e.g., array of objects) or error cases (invalid CUI, no data). Cost info is helpful, but completeness is moderate.
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 100%, so baseline is 3. The description adds context by listing returned fields and mentioning multi-year history, but does not elaborate on parameter 'an' (year) usage or error handling. It adds some value but not significantly beyond the 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 clearly states the tool retrieves yearly financials for Romanian companies by CUI, listing specific data fields (net turnover, profit/loss, employees, equity, assets, debt) and mentions multi-year history. This distinguishes it from sibling tools like ro_company_lookup (basic info) and ro_company_search (name-based search).
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 when to use (for financial data by CUI) but does not explicitly guide on when not to use or compare to alternatives like ro_company_lookup. It mentions cost, which helps with decision-making, but lacks explicit usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.