msio_tech_performance

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

Annotations already indicate readOnlyHint=true and destructiveHint=false, and the description adds meaningful behavioral context beyond that: default last 30 days, regex-based job type classification with v7 taxonomy and multi-label support, and first-assigned-tech attribution with no splitting of multi-tech jobs. These are non-obvious caveats an agent needs to interpret results correctly.

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 well-structured with clear section headers, front-loaded with a one-line summary, and every sentence adds value. USE WHEN, DO NOT USE WHEN, and GOTCHAS are compact and immediately actionable without filler.

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 read-only analytics tool with an output schema present, this description covers purpose, usage, exclusions, default behavior, caveats, and parameter semantics adequately. No critical information is missing for an agent to decide whether and how to call 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 0%, so the description carries the parameter-documentation burden. It compensates partially: 'Default is last 30 days' explains the date range parameters, 'per-technician' implies employee_id, and the job type breakdown note relates to include_job_types. It does not explicitly document all parameters or date formats, but the meaning is largely recoverable.

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 resource and metrics: 'Per-technician performance metrics — revenue, job count, avg value, completion rate.' It clearly distinguishes itself from employee lookup and scheduling by naming what it is not, and the stated use cases align exactly with the tool's function.

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 provides explicit USE WHEN scenarios and DO NOT USE WHEN exclusions with named alternatives: hcp_list_employees for employee details and hcp_update_job_schedule for scheduling. This gives an agent clear decision rules for selecting this tool versus siblings.

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