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fabdendev

dagster-mcp

by fabdendev

list_sensors

List all sensors with status, target jobs, repository, and code location to check which sensors are active and what they trigger.

Instructions

List all sensors with their status and target jobs.

Returns per sensor: name, status (RUNNING/STOPPED), list of target job names, repository, and code location.

When to use: to check which sensors are active and what jobs they trigger. If a sensor is RUNNING but not producing runs, use get_tick_history to inspect recent ticks — it will show skipped ticks, errors, or runs launched. Raises when a code location is unavailable rather than returning a partial list that could be mistaken for the complete set of sensors.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
envNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.8.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses a key behavioral trait: 'Raises when a code location is unavailable rather than returning a partial list.' It also states the return contents precisely. Slight gap: no mention of auth or rate limits, but these are contextually less critical for a read 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?

The description is efficiently front-loaded with the core purpose, then dives into return fields, usage context, and failure behavior. Each sentence earns its place, and the structure is clear without redundancy.

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 list tool, the description covers the main aspects: return fields, usage scenario, and failure mode. However, the undocumented 'env' parameter is a significant gap that leaves the tool incompletely specified. The output schema exists but the parameter semantics are missing, so completeness is not full.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter 'env' has 0% schema description coverage, and the description never mentions it. The agent has no idea what 'env' controls (e.g., environment name for code location resolution). The description fails to compensate for the lack of schema documentation.

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 states a specific verb and resource: 'List all sensors with their status and target jobs.' It clearly distinguishes from siblings like list_schedules and list_jobs by focusing on sensors and their runtime details, plus the failure behavior. No ambiguity about what the tool does.

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?

Provides an explicit 'When to use' clause: to check active sensors and triggered jobs. It also gives a conditional alternative: if a sensor is RUNNING but not producing runs, use get_tick_history to inspect ticks. This routes the agent correctly and prevents misuse.

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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