set_recall_precision

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

Beyond the annotations (readOnly=false, idempotent=true, destructive=false), it explains that the gate is recalibrated immediately, the change is persisted, it is live without restart, and how named levels, raw beta, and empty values resolve. No contradiction with the annotations.

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?

Dense but organized: purpose first, then parameter semantics, then scope. It is longer than average, but every sentence carries behavioral information; minor jargon like 'knob 3' and 'separation curve' keeps it from being perfectly crisp.

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?

Complete for a mutation tool of this complexity: it covers when to use it, all parameter interactions, reset behavior, persistence, and live effect. No output schema exists, but a setter's return value is not needed to invoke it 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?

The schema already covers all four parameters (100% coverage), so the baseline is 3. The description adds real value by defining the precision-to-beta mapping (strict/balanced/lenient -> 2.0/1.0/0.5), beta override precedence, and clearing behavior, which go beyond the schema.

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+resource ('Set an agent's recall precision ... and recalibrate its quality gate') and later adds the distinguishing scope ('per-agent setting, not a per-recall argument'). This separates it clearly from recall-scoped siblings and from get_recall_precision.

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?

It gives a clear exclusion — this is for per-agent settings, not per-recall arguments — and explains when the empty+beta<=0 form clears the override and returns to default. It doesn't explicitly name sibling tools like calibrate_threshold or get_recall_precision, but the context is enough for typical routing.

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