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 what the tool does (returns formatted analytics report with trends/patterns), includes important behavioral constraints (env parameter requires explicit user specification, days has default and max), and outlines the specific analytics provided (success/failure rates, duration stats, pattern detection, etc.). It doesn't mention error handling or rate limits, but covers core behavior well.

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 and appropriately sized. It begins with the core purpose, then usage guidelines, differentiation from siblings, detailed parameter explanations, and return value - each section earns its place. No redundant information, and the formatting with bullet points enhances readability without wasting space.

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 (analytics with pattern detection), no annotations, 0% schema coverage, but with an output schema present, the description provides excellent completeness. It covers purpose, usage, behavioral aspects, parameter semantics thoroughly, and since an output schema exists, it appropriately doesn't detail return format. The description compensates well for the lack of annotations and schema descriptions.

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?

Schema description coverage is 0%, so the description must fully compensate. It provides detailed semantic information for all three parameters: dag_id ('The DAG identifier to analyse'), env ('Target environment — 'dev', 'uat', 'test', or 'prod' with IMPORTANT usage note'), and days ('Number of days to look back (default: 14, max: 180)'). 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 run statistics and trend analysis for a specific DAG.' It specifies the verb ('Get') and resource ('run statistics and trend analysis for a specific DAG'), and explicitly distinguishes it from the sibling tool 'list_dag_runs' by contrasting their outputs (analytics vs. flat list).

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 guidelines: 'Use this when the user asks about DAG reliability, performance trends, statistics, or historical patterns' with concrete examples. It also specifies when NOT to use it ('Unlike list_dag_runs...') and names the alternative tool, making it clear when to choose this tool over siblings.

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