read_table

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

Beyond the readOnly/idempotent annotations, the description discloses two useful behaviors: limit is capped by the server's MIDAS_MAX_ROWS, and the reply reports the table's total record count so truncation is detectable. That is real operational context the annotations cannot convey.

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?

Compact and front-loaded: the core purpose comes first, followed by parameter notes. The inline newlines make the parameter section slightly choppy, but no sentence is wasted.

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?

With no output schema, the description should describe the return more fully; it only mentions the total-count field and truncation behavior. The undocumented product parameter and the absence of any return-shape details beyond the count leave it adequate but incomplete for a 4-parameter read tool.

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 carries the burden. It explains ids (filter to these records), limit (max records, server-capped) and illustrates table naming, but the required product parameter (enum gen/civil) is never explained, leaving a meaningful gap.

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?

States a clear resource and scope: it returns the records of a single table in the open model, with concrete examples ("NODE", "DESIGN/STEEL/DSTL"). It does not explicitly differentiate itself from siblings such as list_tables, describe_table or result_table, so an agent must infer that this is the record-fetching call.

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 table-path examples imply when the tool applies and the ids/limit notes hint at narrowed reads, but there is no explicit when-to-use or when-not-to-use guidance and no routing to alternatives like result_table or list_tables. Usage is inferred rather than stated.

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