Retrieve CREATE TABLE statements for every table and the column list for daily and workout_metrics to inspect the SQLite database structure before querying.
CREATE TABLE statements for every table, plus the column list of daily and workout_metrics.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the burden. It does disclose the shape of the returned content, including the useful nuance that two specific tables get column lists, but it says nothing about safety, permissions, or side effects (a reader must assume it is a harmless read). Adequate but incomplete for a zero-annotation tool.
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?
One sentence, front-loaded with the primary output (DDL statements) and appended with the secondary detail (column lists). Every clause earns its place.
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?
An output schema exists, so return-value description is not strictly required, and the description already covers it. What remains missing is any link to the workflow (call this before run_sql), which would make it complete for a schema-introspection 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?
The tool takes no parameters, so there is no parameter meaning to convey and the baseline of 4 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?
The description concretely states what the tool returns: CREATE TABLE statements for every table plus column lists for daily and workout_metrics. That is more specific than a generic 'get schema', but it never distinguishes itself from schema-related siblings like run_sql or get_report, which is the only thing keeping it from 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?
There is no when-to-use guidance. An agent reading only this description is not told that this is the tool to call before run_sql, nor when the column lists are preferable to the full DDL. Usage is left entirely to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.