scf_generate_system_recipes

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

Beyond the annotations (readOnlyHint=false, destructiveHint=false), the description adds valuable behavioral detail: required role (editor+), asynchronous execution, expected HTTP status (202), and follow-up polling behavior. It also clarifies that the tool queues work rather than returning final results synchronously. No contradiction with annotations exists.

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 compact, front-loaded with the primary action, and packs essential operational facts (role, async behavior, HTTP status, polling endpoint) into two short sentences. There is no filler or repetition of schema details.

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 two-parameter async tool with no output schema, the description gives the essential call-and-follow-up flow: invoke with org/system IDs, expect 202, poll status endpoint. It could be slightly more complete by stating whether the response includes a generation ID or other correlation token needed for the status poll, but the stated workflow is enough for an agent to proceed.

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%, and both parameters already have descriptive text explaining they are UUIDs obtainable from scf_list_organizations and scf_list_systems respectively. The tool description does not add further parameter-level meaning beyond indicating the action is for a system, so the baseline score of 3 is appropriate.

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 opens with a specific verb ('Queue') and resource ('AI generation of evidence-collection recipes for a system'), making the operation's intent unmistakable. It also distinguishes this from sibling retrieval tools like scf_get_system_recipes by framing it as an asynchronous generation action, not a read.

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 clear context: this is a write operation requiring editor+ role, is asynchronous, and returns HTTP 202. It also explicitly directs the agent to poll scf_get_recipe_generation_status afterward, which is actionable follow-up guidance. It does not mention exclusions or alternative tools for cases like retrieving already-generated recipes, but the core usage context is clear.

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