Rank benchmark assets by metric and period for market-context comparison.
Data freshness: rankings reflect latest ingested benchmark observations.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| order | No | desc | |
| metric | Yes | ||
| offset | No | ||
| period | Yes | ||
| window | No | ||
| frequency | No | daily | |
| benchmark_slug | No | ||
| risk_free_rate | No | ||
| include_metrics | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds a useful data freshness caveat ('rankings reflect latest ingested benchmark observations'), which gives insight into data update behavior. However, with no annotations, it does not disclose whether this is read-only, any authentication requirements, or potential side effects, leaving gaps in 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?
The description is concise, with two clear sentences. The main purpose is front-loaded, and the data freshness note is a useful secondary detail. It is not verbose, though it could benefit from a structured parameter overview given the tool's complexity.
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 tool with 10 parameters and no annotations, the description is insufficient. It does not clarify what 'benchmark assets' are, what valid metrics are, or how 'period' should be formatted. While an output schema exists, the input semantics and tool behavior are under-specified.
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 mentions only 'metric' and 'period' by name, mapping to the two required parameters. With 10 parameters total and 0% schema coverage, it fails to explain the meaning of limit, order, offset, window, frequency, benchmark_slug, risk_free_rate, and include_metrics, providing minimal semantic value.
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 ranks benchmark assets by metric and period for market-context comparison. It uses a specific verb (rank) and resource (benchmark assets), distinguishing it from pension-specific ranking tools, though a generic sibling 'rank' exists.
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?
No explicit guidance is given on when to use this tool vs alternatives like 'rank_bulgarian_pension_benchmarks_by_metric' or 'rank'. The purpose phrase 'for market-context comparison' implies a context but does not state exclusions or preferred scenarios.
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.
