dataset_columnsThe columns, which of them are numeric, the row count and the provenance banner of the OrderPadLedger dataset. Call this first to learn the schema.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral disclosure burden. It clearly enumerates what the tool returns: columns, numeric flags, row count, and provenance banner. As a read-only schema inspection tool, this is adequate despite not discussing side effects or permissions.
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 sentences, no filler, and the most actionable guidance ('Call this first') is included. Every word contributes value.
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 simple zero-parameter tool with no output schema, the description lists the key outputs and the intended first-use context. It could specify return formatting or data types, but the description is adequate for an agent to invoke the tool correctly.
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?
There are no parameters and schema coverage is 100%, so the description does not need to add parameter detail. The baseline of 4 for zero-parameter tools 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 clearly states what the tool provides: columns, numeric indicators, row count, and the provenance banner for the OrderPadLedger dataset. It also frames the purpose as learning the schema. It does not explicitly contrast with sibling tools, but the resource and content are specific enough to distinguish it from the listed siblings.
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 instruction 'Call this first to learn the schema' gives explicit usage context and ordering. It does not mention alternatives or exclusions, but for a zero-parameter schema-introspection tool, the timing guidance is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a distinct role: schema, provenance, exact-match row lookup, substring search, multi-value comparison, numeric stats, and top/bottom ranking. The only mild overlap is dataset_row versus dataset_compare and dataset_search, but their descriptions clarify exact equality, multi-value filtering, and cell containment.
All tools share the dataset_ prefix, making the family immediately recognizable. The suffixes mix nouns (columns, row, provenance, stats, top) and verbs (compare, search), so there is no strict verb_noun convention, but the pattern is predictable and readable.
Seven tools is a well-scoped count for a single-dataset exploration server. Each tool covers a distinct query need without redundancy or unnecessary surface area.
The server covers the full read-only lifecycle of interacting with this dataset: schema discovery, provenance, row lookup, search, comparison, aggregation, and ranking. There are no obvious missing operations for its stated purpose.