dq_add_monitoring

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

Annotations are none, so the description carries full responsibility for revealing side effects and requirements. It simply says 'Add data quality monitoring' without stating whether it modifies files, requires an api_key, creates external resources, or is idempotent. This leaves the agent blind to the operation's footprint.

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 extremely concise, a single five-word sentence with no filler or repetition. However, it is so terse that it omits nearly all operational context, suggesting under-specification rather than deliberate pruning.

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?

For a two-parameter tool with no annotations and no output schema, this description is not sufficient. It doesn't explain what 'monitoring' means in practical terms, when to run it, what happens to the project, or why an api_key might be needed. Sibling tools like dq_generate_checks imply a related workflow, but the context is missing.

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?

The description adds no parameter information; it neither mentions `directory` nor `api_key`. Schema coverage is 50% with only `directory` described ('Project directory'), while `api_key` remains undocumented, and the description does not compensate. The agent must guess the role of `api_key` and how `directory` is used.

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 'Add data quality monitoring' provides a clear verb and resource, but it is essentially a human-readable restatement of the tool name. It doesn't specify what kind of monitoring is added (checks, dashboards, alerts) or how it differs from siblings like dq_generate_checks or dq_generate_reports. The meaning is clear at a high level but vague on operational details.

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?

There is no guidance on when to use this tool vs alternatives. No mention of prerequisites, expected project state, or exclusions. With a long sibling list including dq_generate_checks, dq_generate_reports, and grafana_add_alerts, an agent has no basis for choosing this tool.

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