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Glama

get_project_metrics

Read-only

Retrieve a project's budget amount, budget spent, planned time, and elapsed declared time by name, code, or ID. Use it for read-only time and budget tracking of a single project.

Instructions

Read the budget and time counters of one project, found by name, code or id: budget amount, budget spent, planned time and elapsed (declared) time, durations in seconds. Use list_projects_metrics to compare several projects in one call, and get_project for the project's settings rather than its numbers. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectYesThe project, by name, code or id.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idNoThe project these metrics belong to.
budget_spentNoHow much of the budget is spent.
time_elapsedNoDeclared time, in seconds.
time_plannedNoPlanned time, in seconds.
budget_amountNoThe project's budget.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, and the description's 'Read-only' merely restates that. The one genuinely additive detail is the unit disclosure ('durations in seconds'), which the annotations do not provide. Beyond that it says nothing about permissions, missing-data behavior, or freshness of the counters.

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 tightly packed sentences: purpose and return fields first, then sibling routing, then the safety hint. No filler, and the most decision-relevant information is front-loaded.

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?

With an output schema present, the description need not explain return values, and annotations carry the safety profile. Purpose, lookup key, and sibling disambiguation are all covered, so an agent has everything needed to call it 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 description coverage is 100% and the single parameter is fully documented in the schema as 'The project, by name, code or id.' The description repeats that phrasing verbatim, adding no syntax, format, or ambiguity-resolution detail. Baseline 3 is appropriate when the schema does all the work.

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?

States a specific verb and resource ('Read the budget and time counters of one project') and enumerates exactly what is returned: budget amount, budget spent, planned time, elapsed declared time. It also names the lookup key (name, code or id), so an agent can distinguish it from sibling getters without opening the 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?

Explicitly routes to alternatives with conditions: 'Use list_projects_metrics to compare several projects in one call, and get_project for the project's settings rather than its numbers.' Both the multi-project case and the settings-vs-numbers case are covered, leaving nothing to inference.

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