Count rows in a table without running SQL to size it before indexing, partitioning, or sampling.
Count rows in a table without running SQL. Useful to size a table before indexing, partitioning or sampling.
| Name | Required | Description | Default |
|---|---|---|---|
| table | Yes | Table name. | |
| schema | No | Schema (owner) of the table. Optional — defaults to the server's current schema; omit rather than guess. |
Changes observed during successful MCP inspections.
v2.16.3Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. "Without running SQL" is a genuine behavioral disclosure (no SQL parsing/privilege path), but it omits whether the count is exact or from stats, the cost on very large tables, required table-level privileges, and behavior for views or missing tables.
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?
Two short sentences with zero filler; the core operation is front-loaded before the use-case rationale. Nothing could be cut without losing information.
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 low-complexity two-parameter tool this is nearly adequate, but with no output schema the description never states the return shape (a single integer row count) or error behavior on nonexistent/inaccessible tables, leaving a small but real gap.
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 100%, and the schema itself carries a strong hint for the optional schema param ("omit rather than guess"). The description adds no parameter-level meaning beyond that, so the baseline 3 applies.
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 precise verb+resource ("Count rows in a table") and adds the differentiator "without running SQL," which implicitly contrasts it with run_query. It doesn't explicitly name a sibling alternative, so it lands just short of a 5.
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?
"Useful to size a table before indexing, partitioning or sampling" gives clear when-to-use context tied to concrete workflows. It stops short of naming the alternative for similar information (e.g., get_table_stats, which also exposes row counts) or saying when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.