Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds value by mentioning 'returns normalized NAV points' and 'Data freshness: updated as new source NAV observations are ingested,' which go beyond the schema. However, it does not disclose default behavior when no parameters are supplied, what happens if both fund_id and manager_slug are provided, or any pagination/rate limits. This is adequate but leaves important behavioral gaps.

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 three sentences long, each serving a distinct purpose: what it does, how to call it, and data freshness. It is front-loaded with the core purpose and contains no filler or redundant information. 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?

Given the tool has 6 parameters and no required ones, the description should clarify default behavior and edge cases. It explains the primary parameter grouping and output purpose but omits what happens when no identifiers are provided, frequency semantics, and date range defaults. The presence of an output schema reduces the need to describe return structure, but these missing behavioral details make the description incomplete for safe invocation.

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 description coverage is 0%, so the description must compensate. It clarifies the relationship between fund_id and the manager_slug+scheme_code pair, which is crucial and not obvious from the schema alone. However, it does not explain date_from, date_to, or frequency parameters, leaving their semantics undocumented. Since only half the parameters are semantically described, the description provides partial compensation but not full 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 uses a specific verb ('Get') and explicitly identifies the resource ('official NAV time series for a Bulgarian pension fund (UPF/PPF/VPF)'). It clearly distinguishes this tool from siblings like get_benchmark_series by naming the exact asset type and fund categories. The mention of 'return/risk calculations and charting' further clarifies its intended use case.

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 clear context on how to use the tool by specifying the two accepted parameter combinations: 'either fund_id or (manager_slug, scheme_code)'. It also indicates the purpose ('for return/risk calculations and charting'), implying when this tool is appropriate. However, it does not explicitly state when not to use it or mention alternatives like get_bulgarian_pension_fund_nav_series, so it lacks explicit exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.