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Correct segment classification

correct_segment_classification

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": {
      "group_id": "<group_id>",
      "person_id": "<person_id>",
      "tag_ids": "<tag_ids>"
    },
    "name": "correct_segment_classification"
  }
}

Input Schema

NameRequiredDescriptionDefault
tag_idsYesThe corrected tag ids (from the group's tags). At most one for a single-tag group; an empty list clears the person to "No match".
group_idYesThe segment group the person is classified under (from list_segment_groups).
person_idYesThe canonical person to correct (from query_segment_people / query_people).
on_behalf_ofNoA teammate's email, or an agency client's from list_agency_clients, to run this call in that account: their agents, settings, connected accounts, and credits. Omit it to act on your own account.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / on_behalf_of / description
      Previous value: -"An agency client's email, from list_agency_clients, to run this call in that client's account: their agents, settings, connected accounts, and credits. Omit it to act on your own account."New value: +"A teammate's email, or an agency client's from list_agency_clients, to run this call in that account: their agents, settings, connected accounts, and credits. Omit it to act on your own account."
  2. Changed1 schema field changed
    • addedInput schema / properties / on_behalf_of
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "An agency client's email, from list_agency_clients, to run this call in that client's account: their agents, settings, connected accounts, and credits. Omit it to act on your own account."
+}
  3. Changed1 schema field changed
    • changedInput schema / properties / tag_ids / description
      Previous value: -"The corrected tag ids (from the group's tags). At most one for a single-tag group;\nan empty list clears the person to \"no tag\"."New value: +"The corrected tag ids (from the group's tags). At most one for a single-tag group;\nan empty list clears the person to \"No match\"."
  4. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations only mark it non-read-only and non-destructive; the description adds the important traits: it *replaces* the person's tags rather than appending, an empty list clears to 'No match', rates recompute immediately, and the override persists across later re-tags. That persistence caveat is genuinely useful. The mild tension between 'replaces' and destructiveHint=false is resolved by the note that it can be corrected again, so no contradiction.

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

Conciseness5/5

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

The override nature and the persistence warning are front-loaded, and every sentence carries an operational fact (cardinality, empty-list semantics, immediate recompute, sticky override). The summary/returns markup adds structure without padding.

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 four parameters, 100% schema coverage, annotations, and no output schema, the description supplies the missing piece: the return shape (corrected, group_id, person_id, tags). Nothing an agent needs to call it safely and interpret the result is absent.

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 adds cross-parameter meaning: tag_ids must come from the invoking group's tags, cardinality depends on single-tag vs multi-tag groups, and an empty list has a semantic effect. It largely mirrors the per-parameter schema text, which caps it below 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?

It states a specific verb and object ('Correct the tags on one person') and immediately scopes it as the human-set override for a single (group, person) pair. That distinguishes it from sibling classification tools like classify_segment_group and correct_message_classification without needing the schema.

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?

It gives a clear trigger ('when the classifier got them wrong') plus prerequisites and ID sources (person_id from query_segment_people or query_people, tag ids from the group's tags). It also notes no re-classify is needed. It stops short of explicitly naming the alternative tool to use when you actually do want to re-run classification.

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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