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whodb-cli

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by clidey

whodb_platform_file_inspect

Read-onlyIdempotent

Inspect one hosted tabular file to infer column mappings for dataset promotion, previewing columns and mapping flags before using the promote_to_dataset action.

Instructions

Inspect one hosted tabular file and infer promote-to-dataset column mappings.

Use this before whodb_platform_action with resource "file" and action "promote_to_dataset". Prefer fields such as ["columns", "columnMapExample", "columnMapFlags"] first. Set include_rows only when sample row values are needed. The suggested mappings are convenience output; the hosted platform still validates promotion writes. Accepts workspace {host, org, project} for per-call targeting without changing defaults.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNoTop-level output fields to include. Prefer columns and columnMapExample before requesting rows.
file_idYesProject file id
workspaceNoOptional target for this call only. Omit to use the session default set by whodb_platform_session_use, then process/saved defaults. Discover targets with whodb_platform_hosts, whodb_platform_orgs and whodb_platform_projects.
sheet_indexNoOptional spreadsheet sheet index
include_rowsNoInclude preview rows. Defaults to false to keep context compact.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.135.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so safety is covered. The description adds a genuinely new behavioral caveat — suggested mappings are advisory and the platform still validates writes — plus that workspace targeting does not mutate session defaults. Return-shape and pagination behavior remain unstated, but the added caveats exceed annotation coverage.

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?

Purpose is front-loaded in the first sentence and the remaining sentences each carry distinct value (workflow routing, field preference, write-validation caveat, workspace scoping). It is dense but not padded; the density is appropriate for a five-parameter tool.

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

Completeness5/5

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

With read-only annotations carrying the safety profile, full schema coverage on all five parameters, and no output schema to explain, the description covers the remaining needs: what it does, how it fits before promotion, how to choose fields, and that mappings are non-authoritative. Nothing essential for correct invocation is missing.

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 description coverage is 100%, so the baseline is 3. The description goes beyond it by prescribing field ordering, the conditional use of include_rows ("only when sample row values are needed"), and the per-call non-persistent nature of workspace, which the schema does not emphasize as strongly.

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 ("Inspect one hosted tabular file") plus the precise output purpose (infer promote-to-dataset column mappings), which separates it from generic preview/list siblings. It stops short of explicitly naming close siblings like whodb_platform_file_preview or whodb_platform_promote_file_to_dataset, so differentiation is inferred from the workflow mention rather than stated.

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

Usage Guidelines4/5

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

Gives explicit timing ("Use this before whodb_platform_action with resource 'file' and action 'promote_to_dataset'") and operational guidance on param selection ("Prefer fields such as [columns, columnMapExample, columnMapFlags] first"). It does not state when NOT to use it (e.g., versus file_preview), leaving one inference gap.

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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