proof_adjusted_autonomy

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

With no annotations, the description carries the full burden, and it does well by disclosing the formula, optional inputs with defaults, and the response structure including result, formula, interpretation, and cite_as sentence. It does not explicitly state that the operation is side-effect-free, but the calculation-oriented nature makes that reasonably clear.

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 tightly written with no filler: a defining question, the formula, the returned outputs, and parameter defaults are all covered in four efficient sentences. 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?

Although there is no output schema, the description lists the key response components and the defaults, so an agent can anticipate the result shape. Minor gaps remain: there is no explicit valid range for percentage inputs, and 'claimed autonomy' is not explicitly tied to a parameter, but the formula and defaults make those reasonably inferable.

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 100%, providing a baseline of 3. The description adds meaning beyond the schema by mapping a, c, r, and t into the PAA formula components P(A), P(C|A), P(R|A,C), and P(T|A,C,R), and clarifies that inputs are percentages with optional values.

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 states exactly what the tool computes with a named metric, a precise formula, and an explicit list of returned values (honest percentage, gap, single gate). It does not explicitly differentiate PAA from sibling tools like proof_debt or verification_bottleneck, but the formula and resource are specific enough to establish clear 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?

There is no guidance on when to use this tool versus related siblings such as proof_debt, verification_bottleneck, or token_burn. The description only mentions that all parameters are optional and that defaults mirror an interactive calculator, leaving tool selection entirely to inference.

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