run_live_validation

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

With no annotations, the description discloses key behaviors: source database is never mutated, a throwaway working DB is used, optional live data pull, and the read pipeline runs returning a report. This is thorough, though it could mention cleanup of the working DB or error handling.

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 concise, using three well-structured sentences. The first sentence states the core purpose, followed by operational details. No unnecessary words or repetition.

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 absence of an output schema and annotations, the description covers the tool's purpose, safety, and basic workflow. However, it lacks detail on the report's format, parameter roles, and post-conditions like cleanup, leaving some gaps for a complex tool with four parameters.

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 input schema has 0% description coverage, and the tool description only hints at the 'sync' parameter with 'optionally pulls live SimpleFIN + Todoist'. It does not explain 'as_of_date', 'db_path', or 'keep_work_db' sufficiently. With low schema coverage, the description should compensate with detailed parameter semantics but falls short.

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 validates the pipeline on live data without touching the committed snapshot, using a throwaway copy. This distinguishes it from sibling tools that mutate data (e.g., apply_*, sync_*), making the purpose specific and unambiguous.

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 implies use for validation without side effects, but does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. The context is clear but lacks explicit directives.

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