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yeonkyu-git

MCP Prometheus

by yeonkyu-git

get_alerts

Fetch active alerts from Prometheus with filters for severity, state, alert name, job, server name, and instance to monitor system health and identify issues.

Instructions

Fetch active alerts from Prometheus /api/v1/alerts.

Filters (exact-match):

  • severity/state/alertname/job/server_name/instance

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
severityNo
stateNo
alertnameNo
jobNo
server_nameNo
instanceNo
include_alertsNo
environmentNo
env_hintNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'Fetch active alerts' and 'Filters (exact-match)', but lacks critical details such as whether this is a read-only operation, potential rate limits, authentication requirements, or what 'active' specifically means (e.g., time-based criteria). This leaves significant gaps for an AI agent.

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

Conciseness4/5

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

The description is brief and front-loaded with the main purpose, followed by a bullet point for filters. It avoids unnecessary words, but the formatting could be slightly improved for clarity (e.g., separating the filter list more distinctly).

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

Completeness3/5

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

Given the tool's moderate complexity (9 parameters, no annotations, but with an output schema), the description is partially complete. It covers the core purpose and some parameters but lacks behavioral details and usage context. The presence of an output schema means return values are documented elsewhere, reducing the burden on the description.

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 description lists six filter parameters (severity, state, alertname, job, server_name, instance) and notes they are 'exact-match', adding semantic context beyond the schema's 0% coverage. However, it omits three other parameters (include_alerts, environment, env_hint) and doesn't explain their purposes, leaving some parameters undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Fetch active alerts') and the source ('from Prometheus /api/v1/alerts'), making the purpose understandable. However, it doesn't differentiate this tool from sibling tools like 'list_checks' or 'run_promql' that might also relate to monitoring or Prometheus data, which prevents a perfect score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'list_checks' or 'run_promql' for comparison, nor does it specify prerequisites, contexts, or exclusions for usage.

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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