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by ai.peakflo
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table_query

Read-only

Query rows from a data table with optional filtering, sorting, and pagination.

Filters use the format: [{"column": "status", "operator": "eq", "value": "active"}] Supported operators: eq, neq, gt, gte, lt, lte, like, ilike, in, is_null, is_not_null

Returns paginated results with total count.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "tableId": "<tableId>"
    },
    "name": "table_query"
  }
}

Input Schema

NameRequiredDescriptionDefault
pageNoPage number (1-based, default: 1)
limitNoRows per page (default: 50, max: 1000)
filtersNoJSON array of filter objects: [{"column": "name", "operator": "eq", "value": "foo"}]
orderByNoColumn name to sort by
tableIdYesThe data table ID
orderDirNoSort direction (default: desc)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so safety is covered without the text. The description adds two genuinely new pieces: the filter-object grammar with its supported operator list, and the fact that results are paginated with a total count. It stops short of stating limits or error behavior beyond what the schema's defaults convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core action, then the filter syntax and operator list in compact form. Slightly list-heavy, but each line (format example, operator enumeration, return note) supplies information an agent needs to construct a correct call.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description correctly fills that gap by stating results are paginated with a total count. Combined with 100% schema coverage on the six parameters, an agent has enough to call it, with the remaining gap being sibling differentiation rather than missing mechanics.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description contributes beyond the schema by enumerating the full operator vocabulary (eq, neq, gt, like, in, is_null, etc.) and giving a concrete filter-array example, which the schema's filters property only sketches. It does not elaborate on orderBy/orderDir behavior, but that is already documented in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Query rows from a data table') plus the supported capabilities (filtering, sorting, pagination). It does not distinguish itself from siblings like table_sql or table_sql_execute, which also read table data, so an agent must infer the difference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance: nothing says when to prefer this structured-filter tool over table_sql, table_sql_execute, or table_sql_execute for ad-hoc SQL, nor any prerequisites. Only the implicit read nature of 'Query' hints at usage.

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

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