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Read a curated view from a connected external source

query_context_source
Read-only

Run one pre-approved, read-only view against an external data source connected to this client (e.g. the agency's copywriting frameworks or ad data). Call list_context_sources first to see the view keys and which columns you may filter on. You cannot reach anything the view does not expose. API reference: https://tango.applayer.io/docs/api/tools/query_context_source

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
viewYesView key from list_context_sources, e.g. "copywriting_frameworks".
limitNo
clientNoName, @handle, or UUID of the client.
searchNoFree-text match across the view's filterable columns.
sourceNoSource name, only needed when two sources share a view key.
filtersNoEquality filters. Only columns listed as filterable on the view are accepted.
client_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description still adds non-obvious behavior: the view is pre-approved, filters are limited to declared filterable columns, and 'you cannot reach anything the view does not expose' — a meaningful scoping guarantee beyond the annotations. No mention of rate limits or result-shape limits, so not a full 5.

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?

Three sentences, front-loaded with the action and scope, followed by the prerequisite and the access constraint, then a reference link. Every sentence carries information; only the bare URL is arguably filler.

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?

For a read-only query tool with no output schema, the description covers what the tool does, how to discover views, and what filtering is permitted. It omits return shape and pagination behavior, but the core invocation path (find view key, optionally filter, query) is fully specified.

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

Parameters3/5

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

Schema description coverage is 71%, which is fairly high, so the baseline is 3. The description adds context for `view` (must come from list_context_sources) and the filterable-column restriction on `filters`, but says nothing about `limit`, `client` vs `client_id`, `source` disambiguation, or `search` beyond what the schema already documents.

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

Purpose5/5

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

States a specific verb and resource ('run one pre-approved, read-only view against an external data source connected to this client') along with concrete examples of what views expose. It clearly distinguishes itself from list_context_sources by casting that tool as the discovery step while this one executes the query.

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?

Explicitly prescribes the prerequisite workflow: 'Call list_context_sources first to see the view keys and which columns you may filter on.' This gives an agent a clear ordering rule, though it does not say when to prefer this over other read tools (e.g. read_integration, get_client_context) or when-not to use it.

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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