Dayze — Life Context

Condition Check-in

log_condition_checkin

Save a day's check-in for one condition with the same explicit subject_type/person_id. Self check-ins show on the user's Day Card; another person's do not. severity 0-10, note, treatment_done; logged_on defaults today. One per condition/day. ($0.05; API key required)

Input Schema

TableJSON Schema

Name	Required	Description
`note`	No
`severity`	No	0 (none) to 10 (worst).
`logged_on`	No	YYYY-MM-DD; default today in the user's time zone.
`person_id`	No	Owned contact id; required for person.
`request_id`	No	Client idempotency key (retries return original result).
`condition_id`	Yes	From get_conditions or create_condition.
`subject_type`	Yes	self, or person with person_id.
`treatment_done`	No	What they did for it that day.
`idempotency_key`	No	Alias for request_id.

Output Schema

TableJSON Schema

Name	Required	Description
`account`	No	The Dayze account this data belongs to. With more than one Dayze connection, name it in the answer.
`checkin`	No	checkin_id, condition_id, condition_name, logged_on, severity, note, treatment_done.
`created`	No	false: that day already had a check-in, and only the fields passed changed.
`message`	No
`provenance`	No	Which connector wrote the record and which connected Dayze account received it.
`idempotent_replay`	No	true when this request_id already ran: the first result, nothing new written.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedOct 3, 2026

addedOutput schema / properties / account

Added value: +{
+  "additionalProperties": false,
+  "description": "The Dayze account this data belongs to. With more than one Dayze connection, name it in the answer.",
+  "properties": {
+    "display_name": {
+      "description": "Account display name.",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "handle": {
+      "description": "Account handle, e.g. @goh.",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "note": {
+      "description": "How to disclose the account to the user.",
+      "type": "string"
+    },
+    "qa_fixture": {
+      "description": "True for a known QA test account: its records are fixture data, not a real life.",
+      "type": "boolean"
+    }
+  },
+  "required": [
+    "handle",
+    "display_name",
+    "qa_fixture",
+    "note"
+  ],
+  "type": "object"
+}

addedOutput schema / properties / provenance

Added value: +{
+  "additionalProperties": false,
+  "description": "Which connector wrote the record and which connected Dayze account received it.",
+  "properties": {
+    "account": {
+      "additionalProperties": false,
+      "description": "The Dayze account this data belongs to. With more than one Dayze connection, name it in the answer.",
+      "properties": {
+        "display_name": {
+          "description": "Account display name.",
+          "type": [
+            "string",
+            "null"
+          ]
+        },
+        "handle": {
+          "description": "Account handle, e.g. @goh.",
+          "type": [
+            "string",
+            "null"
+          ]
+        },
+        "note": {
+          "description": "How to disclose the account to the user.",
+          "type": "string"
+        },
+        "qa_fixture": {
+          "description": "True for a known QA test account: its records are fixture data, not a real life.",
+          "type": "boolean"
+        }
+      },
+      "required": [
+        "handle",
+        "display_name",
+        "qa_fixture",
+        "note"
+      ],
+      "type": "object"
+    },
+    "channel": {
+      "description": "Always mcp_connector.",
+      "type": "string"
+    },
+    "connector": {
+      "additionalProperties": false,
+      "properties": {
+        "kind": {
+          "description": "oauth or api_key.",
+          "type": "string"
+        },
+        "name": {
+          "description": "The connected app or API-key label shown to the account owner.",
+          "type": "string"
+        }
+      },
+      "required": [
+        "kind",
+        "name"
+      ],
+      "type": "object"
+    },
+    "source": {
+      "description": "chatgpt for ChatGPT OAuth writes; mcp for another OAuth app or API key.",
+      "type": "string"
+    }
+  },
+  "required": [
+    "source",
+    "channel",
+    "connector",
+    "account"
+  ],
+  "type": "object"
+}

Changed3 schema fields changedOct 3, 2026

addedInput schema / properties / person_id

Added value: +{
+  "description": "Owned contact id; required for person.",
+  "type": "string"
+}

addedInput schema / properties / subject_type

Added value: +{
+  "description": "self, or person with person_id.",
+  "enum": [
+    "self",
+    "person"
+  ],
+  "type": "string"
+}

changedInput schema / required

Previous value: -[
-  "condition_id"
-]New value: +[
+  "condition_id",
+  "subject_type"
+]

AddedSep 30, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations only declare this is a non-destructive, closed-world write. The description goes well beyond them by disclosing the self-vs-person visibility rule on the Day Card, the one-per-condition-per-day uniqueness constraint, the logged_on default, the $0.05 cost, and the API key requirement. It stops short of stating the failure mode on a duplicate day's check-in.

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 definition is dense and front-loaded, leading with what is saved before moving to visibility, fields, defaults, and cost. The telegraphic semicolon phrasing is efficient but slightly clipped, and the opening clause about 'the same explicit subject_type/person_id' is awkwardly worded.

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 an output schema present, return values need no explanation, and the description covers the key operational facts: uniqueness, visibility, field defaults, cost, and auth. The remaining gap is the duplicate-day behavior and how this relates to update_condition for correcting an existing entry.

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 89%, so the schema already documents severity bounds, the logged_on format/default, the person_id requirement, and the request_id idempotency behavior. The description restates the severity range and logged_on default but adds no syntax or semantics the schema lacks, which is the expected baseline when the schema does the heavy lifting.

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 gives a specific verb and resource ('Save a day's check-in for one condition') plus the scoping constraint that the check-in is tied to a single explicit subject_type/person_id. An agent can distinguish this from create_condition, update_condition, record_health_trend, and log_sleep without opening any schema.

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

Usage Guidelines3/5

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

Usage is implied rather than routed: it explains that self check-ins surface on the Day Card while another person's do not, and that only one check-in exists per condition/day. However, it never says what to do when a check-in already exists (update vs. error) or names an alternative tool for reading or amending this data, leaving the agent to infer the workflow.

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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