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fabdendev

dagster-mcp

by fabdendev

Get Run Failure Summary

get_run_failure_summary

Diagnose a failed or canceled Dagster run in one call by combining status, step statistics, error logs, and root-cause details into a single summary.

Instructions

Get a consolidated failure diagnosis for a run in a single call.

This is the BEST tool to use when investigating a failed or canceled run. It combines status, step stats, and error logs into one response, avoiding the need to call get_run_status + get_run_logs + get_run_stats separately.

Returns:

  • status, job_name, duration_seconds

  • failed_steps: list of {step_key, duration, error} for each failed step

  • root_cause_error: the RunFailureEvent error (if any)

  • all_step_durations: timing for every step (not just failed ones)

  • suggestions: automated diagnostic hints (e.g. 'Multiple steps failed', 'Step was retried before failing', 'Run was canceled')

If the run did not fail, returns {message: 'Run did not fail.'}.

When to use: always prefer this over get_run_logs for failed runs. Use get_run_logs only when you need the full event stream.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
envNo
run_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.8.0

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries the burden, and it does substantial work: it enumerates the response sections (failed_steps, root_cause_error, all_step_durations, suggestions) and discloses the non-failure behavior ('returns {message: Run did not fail.}'). It does not mention auth requirements or rate limits, but for a read-only diagnostic tool the behavioral surface is well covered.

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?

Front-loaded with the one-line purpose, then structured return fields and a when-to-use section. Efficient sections with no filler sentences, though the enumerated return list is somewhat verbose given an output schema already exists.

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?

An output schema exists, so the detailed return enumeration is redundant but not harmful. The routing guidance and failure/non-failure behavior make it complete enough to invoke correctly; the only real gap is unexplained parameter semantics, particularly the optional env.

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

Parameters2/5

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

Schema description coverage is 0% and the description never mentions either parameter. run_id is inferable from context, but env is entirely undocumented in both schema and description — its meaning, valid values, and default behavior are nowhere stated, so the description does not compensate for the coverage gap.

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?

States a specific verb+resource ('consolidated failure diagnosis for a run') and immediately differentiates itself from siblings by naming get_run_status, get_run_logs, and get_run_stats as the calls it replaces. An agent can tell exactly what this tool does and how it differs from adjacent tools.

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?

Explicit when-to-use ('always prefer this over get_run_logs for failed runs'), an explicit exclusion condition for the alternative ('use get_run_logs only when you need the full event stream'), and a scoping statement for investigating failed or canceled runs. Alternatives and their selection criteria are fully enumerated.

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