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Record a fact

record_fact

Use when you learn something about a customer, ticket, order or other business record and want it kept, including when a value has changed in the real world, such as a customer moving to a new address. Recording a new value for the same entity and predicate makes it the current value; the old one stays in history as what was true before. If the recorded value was never right, use correct_fact instead. The fact is kept with its evidence and attributed to you, and it can be corrected or undone later. When the result includes a receipt link, include it when you tell a person about the change, so they can check it and undo it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valueYesThe value. Any JSON: string, number, boolean, object or array.
evidenceNoWhere the fact came from, so a person can check it.
entity_idYesStable ID of the thing the fact is about, such as customer:42 or ticket:T-1009. Not a display name.
predicateYesWhat the fact is about, such as status, email, owner or amount_due.
workspaceNoOptional. The workspace to act on, as list_workspaces names it. Leave it out to use this connection's first workspace.
confidenceNoOptional confidence from 0 to 1. Leave unset when you are sure.
observed_atNoWhen the fact was observed at the source, RFC 3339. Defaults to unset.
operation_idYesYour ID for this one write, 8-200 characters. Reuse it when retrying the same write so it is not recorded twice. Never reuse it for a different write.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / workspace
      Added value: +{
+  "description": "Optional. The workspace to act on, as list_workspaces names it. Leave it out to use this connection's first workspace.",
+  "type": "string"
+}
  2. Changed1 schema field changed
    • addedInput schema / properties / value / type
      Added value: +[
+  "string",
+  "number",
+  "boolean",
+  "object",
+  "array"
+]
  3. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations (readOnlyHint=false, destructiveHint=false) establish that this writes but doesn't destroy; the description adds real substance beyond them: a new value supersedes the old while history is retained, the fact is attributed to the caller and carries evidence, and it can be corrected or undone later. It could go further on permissions or failure/duplicate behavior, but the semantics of the write are well disclosed and consistent with the non-destructive hint.

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 triggering situation and the key alternative, and every sentence carries information. It is somewhat long at six sentences with a few overlapping ideas (history retention, correctability, receipt link), so it is efficient but not maximally tight.

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 mutation with no output schema, the description covers the important agent-facing behavior: supersession semantics, evidence retention, attribution, and what to do with the returned receipt link. It stops short of describing error/retry handling beyond what the operation_id schema entry explains.

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 100%, so every one of the 8 parameters is already documented (including operation_id idempotency and entity_id format). The description adds framing — evidence is kept so a person can check it — but no new syntax or format detail warrants going above the 3 baseline.

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?

The description states a specific verb+resource ('record a fact' about 'a customer, ticket, order or other business record') and explicitly contrasts with the sibling correct_fact for the case where a value was never right. An agent can distinguish this from retract_fact/correct_fact without opening a schema.

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

Usage Guidelines5/5

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

Gives an explicit trigger ('when you learn something ... and want it kept, including when a value has changed in the real world') plus a named alternative and the condition that selects it ('If the recorded value was never right, use correct_fact instead'). It also gives post-call guidance about sharing the receipt link.

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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