Query Any Baatjie Table

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

Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint=false), the description discloses a non-obvious behavioral trait: personal identifiers are withheld unless include_pii is true, and the response reports which fields were redacted. It also describes error behavior (unknown table lists valid tables; column errors suggest baatjie_describe_schema), which is useful operational context not captured in structured metadata.

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 long but every section earns its place: a one-sentence purpose, explicit alternative guidance, a concise PII warning, structured Args and Returns, 3 practical examples, error handling notes, and a categorized table list. It is front-loaded with the core action, then organized with headers, making it easy to parse without wasted words.

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 tool with 10 parameters, 2 projects, and many tables, the description covers all operational aspects: what it does, when to use it, how parameters map to examples, what the return structure looks like, how PII is redacted, and how errors are reported. The explicit Returns block compensates for the lack of an output schema, and the table allowlist removes ambiguity about valid values.

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 already provides 100% parameter coverage, so the baseline is 3. The description adds value beyond the schema with real-world filter examples, a table allowlist, and clarifications like 'Narrowing columns is the cheapest way' and the full list of PII fields that include_pii controls. These enrich the schema descriptions meaningfully, though the schema already covers the mechanics.

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 opens with a specific verb and resource: 'Read rows from any table in tanOS or sigscheCore', followed by a clear list of capabilities (filtering, column selection, ordering, pagination). It explicitly distinguishes itself from siblings by naming baatjie_next_actions and baatjie_dashboard as cheaper and better-shaped alternatives for specific use cases.

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?

It explicitly positions itself as 'the general-purpose read' and tells the agent when NOT to use it: 'For sequencing work prefer baatjie_next_actions, and for the ops snapshot prefer baatjie_dashboard'. It also provides multiple concrete examples mapping natural-language intents to parameter values, giving clear guidance on how to invoke the tool.

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