Run any Singularis recipe

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

Goes well beyond the annotations by disclosing that results come with a 'check' and cost, and by flagging the non-obvious statefulness of learn/predict/fuse dispatches and the daemon requirement (SINGULARIS_ENGINE_URL) for multi-step learning. That stateful caveat is exactly the kind of behavioral context annotations cannot convey.

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?

Front-loaded with purpose and examples, and the trailing daemon note is genuinely useful operational context rather than filler. It is slightly dense in the final sentence, but every sentence carries information.

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 return details need not be spelled out, and the description nonetheless summarizes result/check/cost. For a complex open-world dispatch tool it covers usage, routing, and the statefulness gotcha; the only real gap is the undocumented 'size' parameter.

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 carry the load. It does clarify 'recipe' (name from the library, with examples) and 'payload' (JSON), but the 'size' parameter is never explained and no payload shape guidance is given beyond 'JSON'.

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 ('Run any job from the Singularis recipe library by name with a JSON payload') and gives concrete recipe examples. It also distinguishes itself from the named sibling tools by scoping itself to tasks that aren't covered by them, and routes to singularis_recipes for the catalog.

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?

Explicitly says 'Use when a numerical task is not one of the named tools', which is a clear use condition and an implicit exclusion against the named siblings, plus a pointer to singularis_recipes for names and schemas. It stops short of naming a specific sibling alternative or giving a when-not example, so it is strong but not exhaustive.

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