record_load_outcome

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

No annotations are provided, so the description carries the full behavioral burden. It implies a write/record action but does not state that data is persisted, whether it feeds a learning/calibration loop, whether re-submission is allowed, or what identifying keys (design_id, version_id, printer_id are all optional) are needed to associate the outcome.

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?

A single front-loaded sentence with no filler or redundancy, which reads cleanly. For a tool with 17 parameters it is arguably too terse, but as a structural matter nothing is wasted.

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 17-parameter mutation tool with no annotations, no output schema and incomplete schema descriptions, one sentence is far too thin. The description says nothing about the required trio (material, result, days_in_service), the estimated-vs-measured distinction implied by load_knowledge/temperature_knowledge, or the write semantics an agent needs before calling it.

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 only 59%, and the description adds no parameter meaning at all. Several parameters that are clearly semantically loaded (load_knowledge and temperature_knowledge defaulting to 'estimated', verdict, stress_fraction, conditioning, hardware) have no explanation in either the schema or the description, so the agent must guess at formats and valid values.

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 names a specific verb (report/record) and resource (how a printed part performed under a real-world load), so an agent can tell this is a field-outcome capture tool rather than an analysis tool like assess_load_bearing. It does not, however, distinguish itself from closely related recorders such as record_print_outcome or record_hardware_outcome, so sibling differentiation is absent.

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 says what is recorded but never when to call it, e.g. after real service use versus during testing, nor what alternatives exist (record_print_outcome, record_hardware_outcome, ingest_measurement). The 'in real use' phrase hints at a context but is not an explicit usage condition or exclusion.

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