list_tables

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

With no annotations, the description bears the full disclosure burden and does well: it documents the exact per-table output format (T-index, format, row/col counts, version hash, column names, row preview) so the agent knows what to expect. It stops short of explicitly stating the operation never modifies the file or describing error behavior (e.g., missing file, empty table list), which would round it out.

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?

Purpose and usage guidance are front-loaded, followed by a compact output-format spec and param docs; every section earns its place. The format block is essential because there is no output schema to spell out the return contract, and it is presented efficiently.

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 read-only tool with no annotations or output schema, the description covers purpose, output contract, cross-tool usage, and parameter semantics thoroughly, making it callable without consulting siblings. Small gaps: no error/edge-case handling and no explicit non-mutation statement, but neither blocks correct invocation.

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 coverage is 0%, and the description fully compensates: file_path is given the added requirement of being an absolute path, and preview_rows is explained as the number of data rows to preview with default and 0-means-none semantics — both beyond the schema's bare type/default fields.

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?

Opens with a specific verb and resource ('List all tables in a Markdown file'), then names what the output contains (column descriptors, row previews). It differentiates from siblings by directing data-lookup use to search_tables and positioning itself over grep for structure discovery.

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?

Explicitly states when to prefer this tool ('Prefer this over grep for discovering table structure') and routes to the alternative ('Use search_tables to find specific data across tables'). Also instructs that the returned table_index feeds read_table and write tools, making cross-tool flow clear.

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