noticed

track_intro

Destructive

Track a promised introduction — someone offered to connect the user with a person they haven't met yet. Creates (no intro_id) or updates (intro_id) a pending intro tied to the connector, so the offer doesn't evaporate in notes. Partial info is fine ('still waiting on their name'). When the intro lands: add the person to the network, then pass resolved_person_id here to graduate it (marks done).

Input Schema

TableJSON Schema

Name	Required	Description
`notes`	No	Context — where the offer happened, why it matters.
`status`	No	waiting (default: still missing info) · ready (ready to ask) · requested (intro asked) · done (it happened) · dropped.
`intro_id`	No	Existing intro id (from list_intros) to update. Omit to create.
`offered_on`	No	Date the intro was offered (YYYY-MM-DD).
`target_org`	No	Their company/org, if known.
`target_name`	No	The person being offered, as known so far — partial is fine.
`missing_fields`	No	What's still needed before asking (e.g. ['name','linkedin']).
`resolved_person_id`	No	The real contact's person id once the intro happened — implies status done.
`connector_person_id`	No	Who offered the intro (their person id from search_people).

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: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": true,
+  "properties": {
+    "data": {
+      "additionalProperties": true,
+      "description": "The operation result when ok is true.",
+      "properties": {
+        "intro": {
+          "additionalProperties": true,
+          "properties": {
+            "connector_name": {
+              "type": "string"
+            },
+            "connector_person_id": {
+              "type": "string"
+            },
+            "id": {
+              "type": "string"
+            },
+            "notes": {
+              "$ref": "#/properties/data/properties/intro/properties/target_org"
+            },
+            "resolved_person_id": {
+              "$ref": "#/properties/data/properties/intro/properties/target_org"
+            },
+            "status": {
+              "type": "string"
+            },
+            "target_name": {
+              "type": "string"
+            },
+            "target_org": {
+              "type": [
+                "string",
+                "null"
+              ]
+            }
+          },
+          "type": "object"
+        }
+      },
+      "required": [
+        "intro"
+      ],
+      "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?

The description discloses non-obvious behavior: create vs. update based on intro_id, resolved_person_id implying done, and the workflow requirement to add the person to the network before graduation. This goes beyond the annotations. It does not detail what resolves on the destructive path (e.g., 'dropped' status), but the schema and destructiveHint annotation cover at least the existence of that behavior.

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 description is two dense sentences with no wasted words. It front-loads the core purpose ('Track a promised introduction'), states create/update behavior, and then gives a clear graduation workflow. Every clause contributes to the mental model an agent needs.

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 9-parameter mutation tool with zero required parameters, the description covers the key decisions: whether to create or update, whether partial data is acceptable, and how to graduate an intro. The output schema is present, so return values are not a known gap. A slight miss is the lack of explicit behavior around the 'dropped' status and what 'destructive' means, but the description handles most situations.

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 already documents all 10 parameters, so baseline is 3. The description adds value on top: it explains the create/update behavior of intro_id, the 'graduate' behavior of resolved_person_id, and the intended meaning of partial target_name/missing_fields. It does not explain every parameter in prose, but the schema covers them well.

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 identifies a clear resource ('a promised introduction') and a clear action ('track'), then nails the exact semantics: create when intro_id is absent, update when intro_id is present, and graduate when resolved_person_id is passed. This is specific enough to distinguish the tool from the sibling list_intros and from generic note-taking, even though no sibling is named explicitly.

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 gives clear context: use this when someone offers to connect the user with someone they haven't met, and it gives concrete workflow guidance — 'When the intro lands: add the person to the network, then pass resolved_person_id here to graduate it.' It even states partial information is acceptable. However, it does not explicitly discuss alternatives or when not to use it beyond the implicit 'don't let it evaporate in notes'.

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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