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Track a metric

configure_metric
Idempotent

Start, change or stop tracking a metric's value over time, so Maplith can tell you when the number moves. Where the metric's data carries a date the value is recorded per calendar period (a month, a week or a day) and get_metric hands back the series; where it does not, Maplith records one number per scan and says so. Off by default: nothing is recorded until your human asks for it, and only aggregates are kept. Set threshold and direction (up: rising is bad; down: falling is bad) to be told when the number crosses a line; the line is drawn for the kind of figure the metric gives now; redraw it when the formula changes shape. Not every metric can be computed: the answer says why, so tell your human rather than wait. Pass tracked false to stop; recorded values stay. Needs: an autonomous key.

Input Schema

NameRequiredDescriptionDefault
nameYesThe metric name, as get_metric lists it.
trackedYesRecord this number from the next scan on, or stop.
directionNoWhich way is bad: 'up' rising, 'down' falling.
thresholdNoThe line the value should not cross, drawn for the kind of figure the metric gives now (a period's value, or one number for the whole history).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / name / description
      Previous value: -"The metric name, as list_metrics gives it."New value: +"The metric name, as get_metric lists it."
  2. Added

TDQS

A4.5/5.0
Behavior5/5

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

Annotations only declare the safety profile (not read-only, idempotent, non-destructive); the description adds the traits that actually matter here: disabled until a human opts in, aggregates-only retention, values persist after stopping, an auth requirement ('Needs: an autonomous key'), and the shape of the failure path. No contradiction with destructiveHint=false or idempotentHint=true.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose and the off-by-default caveat are front-loaded, and most clauses carry real information (period vs. per-scan recording, auth, stop semantics). It runs long and mixes configuration guidance with troubleshooting in one block, but no sentence is pure filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a non-read-only config mutation with full annotation coverage and no output schema, the description covers defaults, retention, permissions, and failure handling. The only soft spot is what a successful call returns, which is gestured at ('the answer says why') rather than described, but nothing needed to invoke it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the schema already documents direction ('up' rising is bad) and threshold semantics, so the description largely restates them. It adds one genuine nuance the schema lacks: the threshold is drawn for the current figure type and must be redrawn when the formula changes shape. That extra earns a bit above floor but does not carry new meaning for name or tracked.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Opens with a precise verb triple and resource: 'Start, change or stop tracking a metric's value over time'. It also draws the boundary against the sibling it will be confused with ('get_metric hands back the series'), so the agent can pick between writing tracking config and reading values without opening either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit when-to-use (human must ask first; off by default), how to stop ('Pass tracked false'), when to touch the threshold ('redraw it when the formula changes shape'), and what to do on failure ('tell your human rather than wait'). The alternative for reading data is named. Nothing material is left to inference.

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

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