codat_get_data_infoGet a company's accounting metadata (base currency, supported data types, etc.). Codat API: GET /companies/{companyId}/data/info.
| Name | Required | Description | Default |
|---|---|---|---|
| companyId | Yes | The Codat companyId (UUID). |
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, and the description adds context by specifying the API endpoint and examples of returned metadata. No contradictions, and the description provides useful behavioral context beyond the safe-read annotation.
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?
Two efficient sentences: first defines purpose with examples, second provides the API endpoint. No unnecessary words or repetition.
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 simple metadata retrieval tool with one parameter, the description covers purpose, basic behavior, and API source. No output schema exists, but the description implies a JSON response. Could mention response format explicitly, but sufficient for this complexity.
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 single parameter 'companyId' is fully described in the schema as a UUID. The description does not add additional parameter semantics, so it meets the baseline for 100% schema coverage.
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 accounting metadata with examples (base currency, supported data types) and includes the API endpoint. It distinguishes from sibling tools like codat_get_balance_sheet which target specific financial data.
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 retrieving metadata about available data types, but does not explicitly state when to use this versus alternatives (e.g., codat_get_data_status) or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool targets a distinct resource or action (e.g., companies, connections, invoices, financial statements). Even similar-looking tools like the three financial statements are clearly differentiated by their names and descriptions. No overlapping purposes.
All tools follow the consistent pattern 'codat_verb_noun' (e.g., codat_create_company, codat_list_invoices, codat_get_balance_sheet). No mixing of styles or irregular naming.
28 tools cover the main read and refresh operations across Codat's domain (companies, connections, accounting data, integrations). The count feels well-scoped for a data aggregation platform, not excessive.
The tool set focuses heavily on reading and listing data, with only create for companies/connections and refresh triggers. Missing update/delete for many entities (e.g., invoices, bills). An escape hatch exists but is GET-only. Notable gaps for write workflows.