Run Recommendation

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

With no annotations, the description carries the full burden and does so: it discloses that the run intentionally STOPS with status='needs_user_input' at checkpoint 'select_candidates', that it takes ~10-60 s using a local LLM, and that all numbers come from a deterministic calculator. These are exactly the non-obvious traits (interruption point, latency, determinism) an agent would otherwise misjudge.

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-loads what the tool is, then the execution flow, then the agent's obligations, then cost/determinism caveats. Every sentence carries actionable information; nothing is redundant with the schema or title.

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 values need no explanation, and the description still covers the critical output the agent must act on (candidates/alternatives, run_id, status). Combined with full parameter documentation, an agent has everything needed to call it and to handle its result correctly.

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 100%, with all four parameters documented including defaults, bounds, and an example for use_case. The description adds no parameter-level detail beyond mentioning run_id as the handoff value, so baseline 3 is correct.

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 ('fully local multi-agent recommendation run') and enumerates the pipeline stages (plan -> Hub scan -> shortlist -> memory/speed estimates). It also names the sibling it hands off to (continue_recommendation), so an agent can distinguish it from estimate_fit, analyze_model, or continue_recommendation without opening a schema.

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 describes the call sequence: run this first, then show candidates/alternatives to the user, then call continue_recommendation with the returned run_id. It also gives a hard constraint ('Never answer for the user'), which is a when/when-not rule, not merely context.

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