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Set an AI agent's call variables

set_agent_variables
Destructive

Replace an AI agent's whole call variables config, as PUT /v1/agents/{agent_id}/variables does. It is checked and republished at once, so the next call uses it; nothing is stored on a refusal. Send base_revision from get_agent_variables to be refused, rather than overwrite, when the agent changed since. A refused config returns error.body.issues, each with a code and where it points.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
configYesAn agent's call variables, SMS templates and caller lookup. Exported from config_schema.py (the API's copy; tests pin the two equal) for the dashboard and the docs. tests/fixtures/call_variables/config_cases.json is the accept/reject contract.
agent_idYes
base_revisionNoThe revision this edit was based on. When sent and stale, the write is refused with 409 revision_conflict. Omit for last-write-wins.
organization_idNoOptional. Defaults to the authenticated workspace; when supplied it must be that workspace's id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Goes well beyond the annotations by disclosing that the config is validated and republished atomically so the next call uses it, that nothing is persisted on a refusal, and that a refusal surfaces error.body.issues with codes and pointers. This is exactly the kind of mutation, atomicity, and failure-shape context the destructiveHint/readOnlyHint flags cannot 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?

Four dense sentences, front-loaded with the action and scope, with each sentence carrying new information (atomicity, refusal behavior, concurrency control, error shape). No filler, though the packed phrasing is close to terse.

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 destructive, non-idempotent write over a deeply nested config with no output schema, the description covers scope, atomicity, concurrency safety, and the error payload. It omits authorization/permission requirements and any guidance on how the supplied nested config is validated, but nothing essential to calling it correctly 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 coverage is 75%, and the description adds meaning where it matters: it explains the workflow for base_revision (fetch from get_agent_variables, stale values cause refusal instead of overwrite) and characterizes how config is applied. It does not add detail for agent_id, organization_id, or the deep nested config fields, so it stops short of a 5.

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 (replace) and resource (an AI agent's whole call variables config) and pins the scope with PUT-style whole-object semantics, which separates it from partial-update siblings like update_agent. It also names get_agent_variables as the read counterpart an agent will need.

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?

Clear context for use and an explicit condition-based rule: send base_revision (sourced from get_agent_variables) to be refused rather than overwrite a concurrently changed agent. It does not state when to prefer this over update_agent or other config-writing siblings, but the practical usage guidance is otherwise strong.

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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