probability.beta_ppf

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

The annotations already declare readOnly=true, idempotent=true, and openWorld=false, so the description does not need to explain safety. It adds useful behavior beyond the annotations: the scipy/float64 computation path, the 10-significant-digit string rounding, the output range [0, 1], and the error condition for q = 0 or 1.

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, with the purpose stated first and followed by input constraints, the output format, and the error case. Dense but no wasted clauses; the rounding/method detail could be considered optional but is useful.

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?

An output schema exists, so explaining the return value is not strictly required, but the description still covers it (string rounded to 10 significant digits). Combined with input domains and the error case, an agent has everything it needs to call this tool correctly; only the explicit routing to sibling tools is missing.

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 schema gives only bare titles Q/Beta/Alpha), so the description must carry the parameter semantics, and it does: q is an exclusive (0,1) decimal string, and alpha/beta are positive decimal strings. It does not explicitly label alpha/beta as the shape parameters, so a small gap remains.

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?

States a specific verb and resource: '베타분포의 분위수를 구한다' (compute the beta distribution quantile). This is clearly distinct from the sibling CDF/PDF tools (probability.beta_cdf, probability.beta_pdf) and from other *_ppf tools, which target other distributions.

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 gives the valid domain for q and states that q = 0 or 1 is an error, which is usable input guidance. It does not state when to use this tool instead of probability.beta_cdf (for the forward direction) or probability.beta_pdf, so routing is only implied by the term 'quantile'.

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