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

With no annotations, the description carries the full burden for behavioral disclosure. It adds a useful data freshness note ('computed from latest ingested FSC NAV and benchmark data') and clarifies that it supports a variety of metrics. However, it does not disclose whether the operation is read-only, potential failure modes, or any side effects, leaving some transparency 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 concise and well-structured, with the main purpose stated in the first sentence and additional details about supported metrics and data freshness in the following sentences. Every sentence adds value without redundancy or excessive length.

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 complexity (11 parameters, no annotations), the description is under-specified. It provides domain context and metric types but lacks parameter explanations, usage scenarios, and behavioral caveats. Although an output schema exists to cover return values, the overall context is insufficient for an agent to select and invoke this tool correctly.

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 schema description coverage is 0%, and the description provides minimal parameter guidance. It mentions the types of metrics supported (e.g., returns, Sharpe), giving some meaning to the 'metric' parameter, but it does not explain other parameters like 'period', 'fund_id', 'manager_slug', or 'scheme_code'. With 11 parameters, this is inadequate for effective use.

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 computes a metric for Bulgarian pension funds or benchmark targets, using a specific verb (compute) and identifying the resource. It also lists supported metric types (returns, drawdown, volatility, Sharpe/Sortino/Calmar, correlation). However, it does not explicitly distinguish itself from sibling tools like get_bulgarian_pension_fund_metric, which may serve a similar purpose.

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 does not provide any guidance on when to use this tool versus alternatives. It implies usage by stating what it computes and mentioning data freshness, but it lacks explicit context, prerequisites, or exclusions. Sibling tools like get_bulgarian_pension_fund_metric might be more appropriate in certain situations, but no guidance is given.

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