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get_script_metrics

Fetch time-series metrics (users, runs, failures) for a script over the last 7 days or 8 weeks to audit adoption and monitor errors.

Instructions

Fetch execution analytics (users, runs, failures) for a script.

Returns time-series metrics over the last 7 days (DAILY) or 8 weeks (WEEKLY). Useful for adoption audits and error monitoring. For per-execution details use list_script_processes. Requires the script.metrics readonly OAuth scope.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_google_emailYesThe user's Google email address (authenticated account).
script_idYesTarget project ID.
metrics_granularityNo"DAILY" (last 7 days) or "WEEKLY" (last 8 weeks). Default "DAILY".DAILY

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries full burden. It discloses the read-only nature via OAuth scope, time series granularity (7 days/8 weeks), and required permissions. However, it lacks details on pagination or rate limits, which are absent but not critical given the output schema exists.

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

Conciseness5/5

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

Three sentences, each adding unique value: main action, time range and granularity, usage context and alternative. No wasted words.

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

Completeness5/5

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

Given the presence of an output schema and complete schema descriptions, the description covers purpose, usage, alternative, and required scope. It is sufficiently complete for an agent to select and invoke the tool correctly.

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%, so baseline is 3. The description does not add extra semantics beyond the schema descriptions for the parameters. It does not explain default behavior or constraints further.

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?

Description clearly states the verb 'Fetch', resource 'execution analytics for a script', and specific metrics (users, runs, failures). It distinguishes itself from sibling 'list_script_processes' by contrasting per-execution details.

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?

Explicitly states when to use ('adoption audits and error monitoring') and provides an alternative ('For per-execution details use list_script_processes'). This gives clear guidance for tool selection.

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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