explore_ats_over_timeTrack average ATS match scores week by week, split by base vs tailored resume and role category, with optional filters for role, level, and employment type.
Average match score over time (weekly), split by phase (base vs tailored) and role category. Optionally filtered by role/level/type.
| Name | Required | Description | Default |
|---|---|---|---|
| level | No | ||
| role_category | No | ||
| employment_type | No |
Changes observed during successful MCP inspections.
v0.11.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context — that results are weekly aggregates split by phase and role category — but says nothing about the time window, bucketing boundaries, or whether empty buckets appear.
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?
Two short sentences, front-loaded with the metric and granularity, then the filters. No filler or restatement of the 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?
For a read-only aggregation tool with no output schema and undocumented parameters, the definition covers what is aggregated and how it is split, which is the core. It is still missing the time range covered by 'over time' and any expectation about result shape, which an agent would need to interpret the output.
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 0% and the three properties (level, role_category, employment_type) have no descriptions, so the description is the only source. It partially compensates by naming 'role/level/type' as the filter dimensions, but gives no accepted values, casing, or format, leaving the agent guessing at valid inputs.
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 metric (average match score), a granularity (weekly), and the two splits (phase base vs tailored, role category) — enough to distinguish it from most siblings like explore_role_mix_over_time. It does not, however, explicitly separate itself from adjacent ATS analytics tools such as explore_tailoring_lift or compare_ats.
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 only usage sentence is 'Optionally filtered by role/level/type,' which describes parameters rather than when to choose this tool over alternatives. There is no guidance on when the trend view is preferable to explore_tailoring_lift or compare_ats.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.