Alias for compute_metric with explicit Bulgarian pension metric intent.
| Name | Required | Description | Default |
|---|---|---|---|
| metric | Yes | ||
| period | Yes | ||
| window | No | ||
| fund_id | No | ||
| frequency | No | daily | |
| scheme_code | No | ||
| manager_slug | No | ||
| benchmark_slug | No | ||
| risk_free_rate | No | ||
| risk_free_slug | No | ||
| benchmark_target_slug | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for behavioral disclosure. It only states that this is an alias for `compute_metric`, which implies identical behavior but does not disclose any actual behavioral traits such as side effects, permissions, or return format. For a tool with 11 parameters and no annotations, this is a significant gap.
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 sentence with no wasted words, making it concise and easy to process. However, it is under-specified for the tool's complexity, which slightly detracts from its effectiveness. It still earns a high score for brevity and clear front-loading of the alias relationship.
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 has 11 parameters, no annotations, and a simple alias statement, the description is incomplete for practical use. It does not explain how parameters relate to Bulgarian pension metrics, what kind of output to expect (beyond the existence of an output schema), or how this differs from `get_bulgarian_pension_metrics_catalog` and sibling ranking tools. An agent would be under-informed when selecting and invoking this tool.
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?
With 0% schema description coverage, the description must compensate for explaining the parameters, but it does not. The only hint is the name and the phrase 'Bulgarian pension metric intent,' suggesting that the `metric` parameter is Bulgaria-specific, but no explicit semantics are provided for any of the 11 parameters. This adds minimal value beyond the raw 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 this is an alias for `compute_metric` with specific Bulgarian pension metric intent, making the tool's purpose evident. It distinguishes itself from the generic `compute_metric` by focusing on Bulgarian pension funds, and from other Bulgarian-specific tools by referencing the compute_metric function directly. However, it doesn't explicitly define what 'metric' means in this context, relying on the name and reference.
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 minimal guidance on when to use this tool versus alternatives like `compute_metric` or other Bulgarian-specific ranking tools. It implies a Bulgarian pension metric use case but does not explicitly state when to prefer this alias over `compute_metric` directly, nor does it mention excluded scenarios or prerequisites. This leaves the agent without clear selection criteria.
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.
