noticed

dismiss_identity_match

Idempotent

Dismiss a PENDING identity match so it stops surfacing — a SOFT reject. It does NOT assert the two are different people, so noticed may re-propose the pair later. Identify it by candidate_id, OR person_a + person_b, OR profile_a + profile_b (the profile pair from a review-queue row — use this for the email→person queue). To permanently say they are NOT the same person, use mark_different_people instead.

Input Schema

TableJSON Schema

Name	Required	Description
`person_a`	No	persons.id — alternative to candidate_id; pass with person_b.
`person_b`	No	persons.id — pass with person_a.
`profile_a`	No	Source-prefixed profile id (e.g. email:a@b.com) — the profile_a from a pending review-queue row. Use for the email→person review queue (candidate_id null, one side has no person). Pass with profile_b.
`profile_b`	No	Source-prefixed profile id (e.g. github:123) — the profile_b from list_identity_matches. Pass with profile_a.
`candidate_id`	No	merge_candidates id of a pending match (the candidate_id from list_identity_matches).

Output Schema

TableJSON Schema

Name	Required	Description
`ok`	Yes	Whether noticed completed the operation.
`data`	No	The operation result when ok is true.
`error`	No	A human-readable error when ok is false.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed1 schema field changedAug 22, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": true,
+  "properties": {
+    "data": {
+      "additionalProperties": true,
+      "description": "The operation result when ok is true.",
+      "properties": {
+        "dismissed": {
+          "type": "boolean"
+        },
+        "message": {
+          "type": "string"
+        }
+      },
+      "required": [
+        "dismissed",
+        "message"
+      ],
+      "type": "object"
+    },
+    "error": {
+      "description": "A human-readable error when ok is false.",
+      "type": "string"
+    },
+    "ok": {
+      "description": "Whether noticed completed the operation.",
+      "type": "boolean"
+    }
+  },
+  "required": [
+    "ok"
+  ],
+  "type": "object"
+}

First observedAug 22, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=false, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral nuance: dismissal is a soft reject, it does NOT assert the two are different people, and the system may re-propose the pair later. This goes beyond what annotations convey.

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?

Three sentences, no filler, purpose front-loaded. The first sentence states action and effect; the second adds the key behavioral caveat; the third covers identification methods and the alternative. Every sentence earns its place.

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?

With five optional parameters and no required fields in the schema, the description correctly explains the mutually exclusive identification methods and the review-queue scenario. It gives enough context for the soft-reject behavior and names the permanent alternative. A minor gap is not explicitly referencing accept_identity_match, but the output schema and sibling list help fill that.

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% and each parameter has a description, but the description adds the crucial grouping logic: one of candidate_id, person_a+person_b, or profile_a+profile_b identifies the match, with profile pairs specifically tied to the review-queue row. This compensates for the schema's misleading all-optional appearance.

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 ('Dismiss'), a specific resource ('PENDING identity match'), and the immediate effect ('stops surfacing'). It also characterizes the action as a SOFT reject and explicitly contrasts it with mark_different_people, making its purpose distinguishable from sibling tools.

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?

The description explicitly names mark_different_people as the correct alternative for permanent rejection and explains when to use the profile_a+profile_b form (the email→person queue). It does not explicitly mention accept_identity_match as the opposite action, but the sibling name and the 'dismiss' verb make the distinction reasonably clear.

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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TDQS

B3.4/5.0

Disambiguation3/5

The tool set is organized around distinct resources, and the descriptions work hard to separate them, but several close pairs remain easy to confuse: add_memory vs memory_save vs add_note, accept_identity_match vs suggest_identity_match, and dismiss_identity_match vs mark_different_people. An agent will often need to read very subtle signals (who originated the content, pending vs initiating a merge, soft vs durable rejection) to pick the right tool.

Naming Consistency3/5

Most tools follow a clear verb_noun snake_case pattern like create_list, update_person, and delete_view, which is readable and mostly predictable. However, the memory tools break the pattern (memory_save, memory_get, memory_search instead of save_memory/get_memory/search_memory), and a few noun-style names (my_profile, network_summary, account_status) add inconsistency.

Tool Count1/5

At 57 tools, this is an extremely large surface that exceeds the calibration threshold for an extreme mismatch. The scope is broad, but many tools are micro-specialized variations of the same concept, such as four memory-related tools and seven identity-match tools, which makes the count feel inflated rather than well-scoped.

Completeness4/5

The tool set provides thorough lifecycle coverage for the core domain: people can be added, updated, searched, and removed; lists, views, actions, and scheduled tasks have create/read/update/delete; and identity matching has accept, dismiss, differentiate, and suggest paths. Minor gaps exist, such as no direct memory/note deletion or intro deletion, but agents can generally complete workflows without hitting dead ends.

Resources

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