MCP-Airflow-API

all_dag_event_summary

Summarize event logs across all Airflow DAGs to monitor workflow activity and quickly identify failures or anomalies.

Instructions

[Tool Role]: Provides summary of event logs across all DAGs.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "all_dag_event_summary"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.0.0Jul 31, 2026

TDQS

B3.1/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states that a summary is produced, without disclosing aggregation details, pagination, time range scope, auth requirements, or behavior with large DAG counts. The word 'summary' implies read-only, but that is not explicit.

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 a single concise sentence with minimal wasted words, and the key information is front-loaded. The only minor issue is the '[Tool Role]:' prefix, which is boilerplate and adds no semantic value.

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?

For a zero-parameter tool with an output schema, the description is minimally sufficient for selection but leaves ambiguity about what the summary actually contains (e.g., counts, status breakdowns, time range). The output schema may cover the return structure, but the selection would benefit from a note on when to request this aggregate view versus raw event logs.

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

Parameters4/5

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

The tool has zero parameters, so there is no parameter burden and the schema coverage is trivially 100%. The description adds no parameter-level detail, but none is required for this tool.

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 uses a specific verb ('Provides summary') and identifies the resource ('event logs across all DAGs'), which clearly distinguishes it from raw log list/detail tools like list_event_logs and get_event_log. However, it does not explicitly contrast with other summary tools such as all_dag_import_summary, so it lacks full sibling differentiation.

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 gives no guidance on when to use this tool versus alternatives. It does not mention use cases, when the aggregate summary is preferred over raw event logs, or any relevant prerequisites or filters.

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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