Skip to main content
Glama

octri_monitoring_summary

Summarizes production health for a project over a chosen time window, returning event counts, error counts, error rates, and distinct issues so you can decide whether to inspect issues.

Instructions

Production health for the project: event count, error count, error rate and distinct issues over a window. Call this before reading issues. It tells you whether there is anything to look at.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rangeNoTime window. Defaults to 24h.
project_idNoProject id. Optional, falls back to the CLI's selected project.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.4

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It implies a read-only summary and describes the metric payload, but never states that it is non-mutating, whether it requires project permissions, or how large/expensive the query is across long ranges like 90d. Adequate but incomplete for an annotation-free tool.

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 short sentences, zero filler, and the highest-value information (what metrics, then when to call) is front-loaded. Every sentence earns its place.

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 simple two-parameter read summary with no output schema, the description usefully enumerates the returned metrics so the agent knows what it gets back. It omits project-scoping behavior (project_id vs CLI-selected project) and any cost/latency expectation for wide ranges, which keeps it short of a 5.

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%, so both parameters (range enum with default 24h, optional project_id fallback) are already fully documented in the schema. The description's 'over a window' hints at the range parameter but adds no syntax, default, or scoping detail beyond the schema. Baseline 3 applies.

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?

Names a specific verb/resource combination ('Production health for the project') and enumerates the exact metrics returned (event count, error count, error rate, distinct issues) plus the scoping window. An agent can distinguish this from siblings like octri_list_issues or octri_monitoring_performance without opening any schema.

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

Usage Guidelines4/5

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

Gives explicit sequencing guidance: 'Call this before reading issues. It tells you whether there is anything to look at.' This is a clear use-context, though it does not state when-not to use it or name the alternative monitoring tools (octri_monitoring_releases, octri_monitoring_performance) that could be confused with it.

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