Skip to main content
Glama
Hardik-Singh

Invariance MCP

Official
by Hardik-Singh

invariance_monitor_preview_target

Read-only

Dry-run a monitor target against history to see which runs and nodes it would inspect. Returns IDs and counts, writes nothing.

Instructions

Dry-run a monitor target against history to see which runs/nodes it would inspect. Writes nothing. Returns {run_ids, node_ids, counts:{runs,nodes}, truncated}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesJSON object string with one of {target} or {monitor_id}, plus optional sample_limit. target shape matches create: {"kind":"current_run"} | {"kind":"specific_run","run_id":"run_..."} | {"kind":"agent_history","filters":[...]}. Example: {"target":{"kind":"agent_history","filters":[{"field":"environment","operator":"eq","value":"prod"}]},"sample_limit":100}

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, and the description reinforces this with 'Writes nothing.' It adds valuable context about the return payload and the possibility of truncation, which goes beyond what annotations provide. No contradictions.

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?

Two tight sentences that front-load the purpose and follow with side-effect and return information. There is no wasted wording.

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 single-parameter preview tool with read-only annotations, the description covers what it does, its side-effect-free nature, and the return format. It does not mention error conditions or which history is used, but given the schema's detail this is a minor gap.

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 input schema already provides 100% description coverage for body, including the JSON shape and examples. The tool description adds no parameter-level detail, so it neither improves nor worsens the baseline.

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?

Clearly states it dry-runs a monitor target against history to see which runs/nodes would be inspected. This distinguishes it from sibling tools like invariance_monitor_evaluate that likely execute the monitor. The phrase 'Writes nothing' further clarifies its read-only nature.

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?

Provides clear context that this is a dry-run tool for previewing target selection before actual execution. However, it does not explicitly name alternative tools or state when not to use it, leaving the routing to inference.

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

Deploy Server

Other Tools