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noticed

by so.noticed.mcp

accept_identity_match

Destructive

Accept a PENDING identity match — merge the two records into one. 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 where candidate_id is null). The target/first record survives; your own person always survives. REVERSIBLE (an admin can undo it). If noticed has evidence the two may be DIFFERENT people it does NOT merge — it returns a needs-confirmation result with the conflicting evidence + a confirmation_token; relay the human-readable evidence without mentioning tokens or override mechanics, and only if the user still wants to merge, call again passing the token back (never pre-set it). A verified-sign-in conflict is admin-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
person_aNopersons.id — alternative to candidate_id; pass with person_b.
person_bNopersons.id — pass with person_a.
profile_aNoSource-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_bNoSource-prefixed profile id (e.g. github:123) — the profile_b from list_identity_matches. Pass with profile_a.
candidate_idNomerge_candidates id of a pending match (the candidate_id from list_identity_matches).
confirmation_tokenNoReturned BY a needs-confirmation response. Pass it back to merge anyway, only after the user reviewed the evidence. Cannot be guessed/pre-set.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYesWhether noticed completed the operation.
dataNoThe operation result when ok is true.
errorNoA human-readable error when ok is false.

Schema Changelog

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

  1. Changed1 schema field changed
    • 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": {},
+      "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"
+}
  2. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare destructiveHint=true and readOnlyHint=false. The description adds significant behavioral context: it clarifies the target/first record survives and the user's own person always survives, notes reversibility (admin can undo), and explains the needs-confirmation response with a token, including the instruction not to pre-set the token. These details go well beyond the annotations.

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?

The description is long but information-dense, with the core purpose and identification options up front, followed by behavioral caveats. Every sentence contributes meaningful guidance, but the density makes it slightly harder to parse quickly. It is well-structured overall.

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?

For a complex merge operation with a destructive hint, the description covers all essential aspects: identification methods, survival rules, reversibility, the confirmation flow with token, and the admin-only restriction for verified sign-ins. The output schema exists, so return values need not be explained. Nothing critical 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?

The schema covers 100% of parameters, but the description adds valuable usage semantics: which combination of parameters to use (candidate_id vs person_a+b vs profile_a+b), that profile_a+b is for the email→person queue where candidate_id is null, and the confirmation_token usage. This enhances the schema descriptions rather than simply repeating them.

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 the verb 'Accept' and the resource 'a PENDING identity match' with the outcome 'merge the two records into one'. It clearly differentiates from sibling tools like dismiss_identity_match (reject) and mark_different_people (mark as different) by specifying the merge action.

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 explains when to use it (for a pending match), how to identify the match (candidate_id, person_a+b, or profile_a+b with a note on which queue), and the confirmation flow when conflicting evidence exists. It also mentions admin-only for verified-sign-in conflicts. It does not explicitly name sibling alternatives like dismiss_identity_match, but the context is clear enough.

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