Inspect a SQLite table or view and return columns, foreign keys, and indexes as CSV sections, so agents can understand schema before writing queries.
Columns (cid, name, type, notnull, default, pk), foreign keys and indexes of a table or view, as CSV sections.
| Name | Required | Description | Default |
|---|---|---|---|
| table | Yes | Table or view name. |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish that this is a safe, read-only, idempotent operation. Beyond that, the description adds useful behavioral context by stating the output is returned as CSV sections and specifying the column attributes included. It does not cover error behavior for missing tables or section formatting details, but it adds more than the annotations alone provide.
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 a single, front-loaded sentence with no filler. It immediately states the resource and the returned information, making every part of the sentence earn 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?
With no output schema, the description carries responsibility for explaining return values and does so by listing the returned metadata and its CSV-section format. It is nearly complete for a simple introspection tool, though it omits details like section delimiters, column ordering, and handling of nonexistent tables.
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 100%, so the input schema already documents the single 'table' parameter as a table or view name. The description reinforces that the target can be a table or view, but adds no further meaning beyond the schema. Baseline 3 is appropriate when the schema carries parameter semantics.
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 clearly identifies the resource (a table or view) and enumerates the metadata returned: columns with named fields, foreign keys, and indexes. It is specific about output content, but it does not distinguish itself from siblings like get_schema or list_tables, so it falls short of the sibling-differentiation bar for 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 explicit guidance on when to use this tool versus alternatives such as get_schema, list_tables, or read_query. The intended use is only implied by the description of returned metadata. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.