Aletheia Certified Compute

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

With no annotations, the description carries the full disclosure burden and does meaningful work: it states the two outcomes (a proved answer or a named refusal naming the capability boundary) and an explicit, unusual cost model (0.001 USDC charged only when an answer speaks; refusals free). Missing latency, determinism, or limits, but the behavioral profile is far richer than the schema provides.

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, the core action front-loaded, then outcomes, then cost. Nothing is redundant and the billing caveat earns its place because it affects an agent's willingness to invoke.

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?

For a one-parameter, no-annotation, no-output-schema tool, the description supplies what the structured fields cannot: the two return outcomes and the billing trigger. It does not describe the shape of a proved answer or refusal payload, but that is a minor gap given the tool's simplicity.

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 single parameter has 100% schema description coverage including a concrete example, so the schema already carries parameter meaning. The description adds no syntax or format detail about the prompt beyond what the property description shows, which is the baseline-3 case.

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 gives a specific verb pair (induce and certify) applied to a concrete resource (a program) sourced from worked examples, so an agent can tell this synthesizes and verifies code rather than running it. 'Induce' is somewhat jargon-heavy, and with no siblings listed there is no differentiation to make, but the purpose is recoverable.

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?

Usage is implied: it says the input is worked examples and that out-of-scope tasks yield a named refusal, which hints at when the tool applies. However, it never states when to prefer this over computing the answer directly, nor what kinds of example sets qualify, so the routing guidance is only inferred.

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