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Add a user memory

memory_add

Store a new long-term memory for the authenticated user — a durable fact or preference that Synaplan will recall in future conversations.

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": {
      "category": "<category>",
      "key": "<key>",
      "value": "<value>"
    },
    "name": "memory_add"
  }
}

Input Schema

NameRequiredDescriptionDefault
keyYesShort identifier for the memory (min 3 characters), e.g. tech_stack.
valueYesThe fact or preference to remember.
categoryYesCategory for the memory, e.g. preferences, work, personal, health.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare this is a non-readonly, non-destructive, non-idempotent write, so safety is covered. The description adds genuinely useful context: the write is user-scoped and durable across conversations. It does not disclose what happens when the same key is written twice (relevant given idempotentHint=false) or any storage limits.

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?

A single front-loaded sentence with the action and its scope first and the persistence rationale second. Nothing is redundant with the title or schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

All three required params are documented in the schema and annotations cover the mutation profile, so an agent can call this correctly. However, there is no output schema and the description says nothing about the return (e.g. an id) or duplicate-key behavior, which leaves real ambiguity for an insert-style tool.

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 100% — key, value and category each carry their own example and constraints. The description adds no meaning beyond the schema, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Store a new long-term memory") plus scope ("for the authenticated user") and persistence semantics ("recalled in future conversations"), which clearly separates it from the read-side sibling memory_search. It never names that sibling explicitly, so it falls short of full differentiation.

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?

Implies the eligibility criterion — the value must be a durable fact or preference, not transient data — which is a useful usage hint. There is no explicit when-not guidance (e.g. don't re-store something already known, search before adding) and no mention of the memory_search alternative for checking existing entries.

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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