track_metric

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

With no annotations, the description must carry the full burden. It discloses key behavior: counters increment by +N (default +1) and values act as gauges. This adds useful context. However, it omits side effects like auto-creation of stats (only in schema) and does not explicitly state that this is a write/mutating operation or any persistence behavior, leaving some behavioral ambiguity.

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 two sentences with no wasted words. The first sentence front-loads the purpose and use cases; the second efficiently explains the counter/gauge semantics. It is appropriately sized and well structured.

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?

Given the tool's moderate complexity (4 params, 1 required), the high schema coverage, and the absence of an output schema, the description adequately covers the core purpose and usage. It lacks only minor context like return behavior or explicit mention of timestamp, but these are not critical given the schema covers parameter details.

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 100%, so the baseline is 3. The description reinforces the counter/gauge distinction and how count vs value map to these modes, which adds a little meaning. But the schema already explains each parameter thoroughly, so the description does not significantly elevate clarity beyond it.

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: 'Record a metric point your app produced.' It clearly states the tool's job and distinguishes it from sibling read/query tools (read_stat, list_stats, ask_ezstat) by focusing on recording vs retrieving metrics. Concrete examples (page view, checkout, latency) further clarify the purpose.

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 gives explicit when-to-use guidance: 'Use this whenever the surrounding code emits a counter or gauge.' It provides relevant examples and explains the counter vs gauge distinction. However, it does not explicitly name alternative tools or state when not to use it, so it stops short of a full 5.

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