Get historical benchmark series for pension-fund comparison workflows.
Use with compute/rank tools to compare Bulgarian pension funds against inflation or market proxies over aligned periods. Data freshness: updated as new benchmark source observations become available.
| Name | Required | Description | Default |
|---|---|---|---|
| date_to | No | ||
| date_from | No | ||
| frequency | No | daily | |
| benchmark_slug | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries the transparency burden. It adds one behavioral detail: 'Data freshness: updated as new benchmark source observations become available.' This is useful but doesn't disclose more about the series structure, alignment behavior, or potential errors. For a read-only get tool, this is moderate transparency.
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?
Three short sentences front-load the purpose and usage, with a closing note on data freshness. No wasteful content, every sentence earns its place.
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 provides a clear purpose, usage, and data freshness note. However, with a 0% parameter coverage and a very similar sibling tool, the agent may not know when to choose this generic version over `get_bulgarian_pension_benchmark_series`. The output schema exists but is not described in text, which is acceptable, but the overall guidance for selection among siblings 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 coverage is 0% – the description does not explain any of the four parameters (benchmark_slug, date_from, date_to, frequency). It only hints at 'aligned periods' but gives no details on formats, defaults, or required parameters. This fails to compensate for the schema's lack of descriptions.
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 'Get historical benchmark series' with a specific purpose for pension-fund comparison workflows. It references Bulgarian pension funds and market proxies, giving resource and scope. However, it doesn't explicitly distinguish itself from the similarly named sibling `get_bulgarian_pension_benchmark_series`, so it's not a perfect 5.
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?
Provides explicit usage context: 'Use with compute/rank tools to compare Bulgarian pension funds against inflation or market proxies over aligned periods.' This tells the agent when to use it in comparative workflows, but doesn't mention any exclusions or alternative tools.
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.
