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Uptimepage

by dev.uptimepage

Incident metrics

get_incident_metrics
Read-only

Incident metrics over a trailing window (default 30 days): MTTA/MTTR in seconds, total incidents, counts by severity and state, auto- vs human-resolved, and the noisiest monitors. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
window_daysNoTrailing window in days (1..=365). Defaults to 30 when omitted.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
totalYesIncidents opened in the window.
by_stateYes
mtta_secsNoMean time to acknowledge, seconds. `null` if none were acknowledged.
mttr_secsNoMean time to resolve, seconds. `null` if none were resolved.
by_severityYes
window_daysYes
top_monitorsYesNoisiest monitors, most incidents first.
auto_resolvedYesResolved automatically on recovery, with no human resolver.
human_resolvedYesResolved by a person.

TDQS

A4.1/5.0
Behavior3/5

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

The annotations already declare readOnlyHint=true, and the description repeats 'Read-only'. The description adds useful context about the default 30-day window and the metric categories, but it does not disclose other behavioral aspects like response structure or pagination. Since an output schema exists, the bar is lower, and this provides modest added value.

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?

The description is a single, front-loaded sentence that packs essential details (window default, metrics list, read-only) without redundancy or filler. Every phrase earns its place.

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?

For a simple aggregate tool with one optional parameter and an output schema, the description sufficiently covers purpose, scope, and key behavior. It does not need to explain return values since an output schema exists, and the sibling context clarifies usage.

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?

The single parameter (window_days) is fully described in the schema with trailing window and default value. The description only echoes the default without adding new syntax or semantic detail. With 100% schema coverage, baseline 3 is appropriate.

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?

The description clearly states a specific action ('get incident metrics') and resource plus the exact metrics included (MTTA/MTTR, counts by severity/state, resolution source, noisiest monitors). This differentiates it from sibling tools like get_incident (single incident) and list_incidents (list).

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?

The context is clear: this tool provides aggregated incident metrics over a trailing window, implying use for summary/trend analysis. It does not explicitly name alternatives or exclusions, but the sibling list makes the differentiation evident, warranting a 4 rather than a 5.

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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TDQS

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct resource and action: flow runs, step trends, incidents, incident metrics, monitors, monitor history, org health, org usage, status pages, notification channels, regions, status pages lists, and tags. The get_ vs list_ distinction is consistent and each pair (e.g., get_monitor vs list_monitors) is clearly separated by depth of detail. No two tools appear to serve the same purpose.

Naming Consistency5/5

All tool names follow the verb_noun pattern with snake_case, using only 'get_' for single-item or aggregate detail and 'list_' for collections. Objects are consistently named (monitor, incident, status_page, org_*). This predictive pattern makes it easy to guess tool behavior from the name.

Tool Count5/5

At 15 tools, this server sits at the upper bound of the well-scoped range, yet every tool fills a clear niche: monitoring details, history, incidents, flow-specific analytics, org-level views, and reference data (regions, tags, channels). No tool feels redundant, and the count is appropriate for a read-only monitoring API.

Completeness4/5

The read-only surface is remarkably comprehensive, covering monitors, incidents, flow runs, step trends, status pages, notification channels, regions, tags, and org health/usage. The only notable gap is the lack of any mutation tools (e.g., update_monitor, acknowledge_incident) which the descriptions hint at but do not expose, so agents cannot act on the information—only observe.

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