Return the full text of Bulgarian pension legal documents.
| Name | Required | Description | Default |
|---|---|---|---|
| document | No | Optional filter – "ordinance_9", "ordinance_33", or "kso". If omitted, returns all available documents. |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of indicating behavior. It states 'Return', implying a read-only operation, but doesn't disclose potential nuances like access restrictions, error behavior, or that it returns all documents unless filtered. Overall, it's basic but not misleading.
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, front-loaded sentence with no redundant words. It efficiently communicates the core function without wasting tokens.
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 the tool's low complexity (one optional parameter), an existing output schema, and clear schema coverage, the description plus schema is largely complete. It lacks a nod to related tools like search_pension_law, but that gap is already handled in the usage dimension.
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 input schema fully describes the optional 'document' parameter, including allowed values and default behavior. The description adds no parameter-specific information beyond what the schema already covers, so the baseline score of 3 applies.
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 identifies a specific verb ('Return') and resource ('full text of Bulgarian pension legal documents'), which distinguishes it from siblings like search_pension_law. It unambiguously states the tool's function.
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 explicit guidance on when to use this tool versus alternatives. Although the sibling search_pension_law suggests a differing use case, the description does not mention it or offer any comparative context.
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.
Many tools have identical aliases (e.g., list_funds and get_bulgarian_pension_funds, list_benchmarks and get_bulgarian_pension_benchmarks), creating ambiguity. An agent would struggle to choose between them. Additionally, cache_stats is unrelated to the core domain, adding confusion.
Naming patterns are inconsistent: some tools use short verb_noun (list_funds, compute_metric), while aliases are long and verbose (get_bulgarian_pension_fund_managers). Mixing both styles without clear distinction harms predictability.
26 tools is on the high side, but many are aliases; the unique tool count is around 16-17, which is reasonable for a comprehensive analytics server. However, the alias redundancy makes the list feel bloated.
The tool set covers discovery (list_funds, list_managers, list_benchmarks), data retrieval (get_nav_series, get_holdings_reports_index), computation (compute_metric, rank), simulation (simulate_saver_outcome), and legal documents (search_pension_law). Missing are tools for updating or creating data, which is acceptable for an analytics server. A minor gap is the lack of a direct fund detail tool besides NAV.
