Ops MCP Server

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 effectively describes key behaviors: it's a read operation (implied by 'Get'), returns interactive numbered lists, and includes important constraints like the 'IMPORTANT: Do NOT guess or default' warning for the 'env' parameter. However, it doesn't mention rate limits, authentication requirements, or error handling scenarios.

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

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

The description is well-structured with clear sections: purpose statement, usage guidelines, parameter explanations, and return format. It's appropriately sized for a 4-parameter tool with no annotations. Minor improvement could be made by slightly tightening the language, but every sentence adds value.

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

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

Given the tool's complexity (4 parameters, no annotations, but with output schema), the description is complete. It covers purpose, usage, all parameters with semantics, and return behavior. The output schema existence means the description doesn't need to detail return values, and it appropriately focuses on how to present results to users.

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

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

With 0% schema description coverage, the description fully compensates by providing detailed parameter semantics. It explains all 4 parameters: 'env' (target environments with specific values and an important usage warning), 'dag_id' (optional filter), 'date' (valid values and default), and 'limit' (purpose and default). This adds significant value beyond the bare schema.

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

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

The description clearly states the tool's purpose: 'Get DAG runs for today, yesterday, last week, or a specific date.' It specifies the verb ('Get'), resource ('DAG runs'), and scope (time-based filtering). It distinguishes from sibling tools like 'get_dag_run_details' (which provides deeper investigation) and 'list_dags' (which lists DAGs rather than runs).

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

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

The description provides explicit usage guidance: 'This is the go-to tool when the user asks about DAG runs, processing status, or historical failures.' It also specifies the return format ('numbered interactive list') and how to use the output ('Present these to the user so they can pick one by number'). This gives clear context for when to use this tool versus alternatives like 'get_dag_run_details' for deeper investigation.

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