wren

Recent Wren notebooks

list_recent_notebooks

Read-onlyIdempotent

The user's latest notes, newest first: id, title, subject, pages, last edit, the outline of pages Wren wrote, and the note this chat has been writing to. Use it when the user returns to a topic, then add pages to that noteId.

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": {
      "context": "<context>",
      "llm_model": "<llm_model>"
    },
    "name": "list_recent_notebooks"
  }
}

Input Schema

Name	Required	Description
`limit`	No	Notes per call (default 5).
`cursor`	No	nextCursor from the previous call.
`context`	Yes	Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
`llm_model`	Yes	The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
`conversation_id`	No	Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request.

Output Schema

Name	Required	Description	Default
`ok`	Yes
`notebooks`	Yes
`nextCursor`	No
`conversationNote`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 14, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive closed-world behavior, so the safety profile is covered. The description adds real value beyond that by disclosing ordering semantics and the noteworthy behavior that one returned entry is the note this chat has been writing to, though it says nothing about result volume or pagination behavior.

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?

Two sentences, front-loaded with the resource and ordering, followed by actionable usage. The returned-field enumeration is somewhat long and partly redundant given that an output schema exists, but it is not padded with filler.

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 read-only listing tool with full schema coverage, complete annotations, and an output schema, the description covers what is needed: what comes back, in what order, and what to do next. Nothing essential to calling it correctly is missing.

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%, so limit, cursor, context, llm_model, and conversation_id are fully documented in the schema itself. The description adds no meaning about any parameter beyond implicitly suggesting pagination through "newest first", so the baseline of 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?

The description states the resource (the user's latest notes) and the ordering (newest first), and enumerates the returned fields, so the agent knows this is a recent-notes retrieval rather than an arbitrary search. It does not differentiate itself from the sibling list_notes, leaving the agent to infer the distinction.

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 gives a concrete trigger ("when the user returns to a topic") and prescribes the follow-on action (add pages to that noteId), which is genuinely useful chaining guidance. It omits any when-not-to-use guidance or a comparison against list_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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