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Glama

mnemosyne_todo_update

Destructive

Manage your to-do backlog by editing, completing, moving, or removing tasks in one batch. Each operation reports its own result, so a stale task ID won't block the rest.

Instructions

Change the user's To-do backlog: edit a task, tick it off, move it to another list, or take it out. Every operation names a task by the id from mnemosyne_todo_list, so call that first. Removing a task archives it by default, and it can be restored. Pass permanent: true only when the user asked for it to be deleted outright. The whole batch is applied in order as one save, and each operation reports its own outcome, so a stale id does not sink the ones around it. Works with the app closed on a dev install (the headless daemon reads the file); an npm install has no daemon and needs the app running. Scope todo:write.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
opsYesThe changes, applied in order. Up to 100 per call.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.10.0

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint=false, destructiveHint=true), the description discloses that removal archives by default, that archived tasks can be restored, that the batch is applied in order as one save with per-operation outcome reporting, that a stale id won't sink the rest, and that daemon availability depends on the install type. This is far more transparency than the annotations alone provide.

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?

Every sentence earns its place: purpose, prerequisite, archive behavior, permanent-delete guardrail, batch semantics, failure isolation, environment note, and scope. The most decision-relevant information is front-loaded, and there is no filler or repetition of schema text.

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?

The tool is complex, has no output schema, and carries a destructive annotation, yet the description covers invocation prerequisites, side effects, ordering, failure behavior, and environment constraints. The only gap is that the exact response shape is not specified, though 'each operation reports its own outcome' provides a useful partial contract.

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 covers 100% of parameters with detailed descriptions, so the baseline is 3. The tool description adds meaningful operation-level semantics: ids come from mnemosyne_todo_list, batch order matters, stale ids are isolated, and permanent deletion requires explicit user intent. This compensates above baseline without duplicating the schema.

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 a clear verb and resource: 'Change the user's To-do backlog' and then enumerates the concrete operations (edit, complete, move, remove). It also differentiates from sibling tools by requiring task ids from mnemosyne_todo_listable, making the scope unmistakable.

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 explicit and practically important guidance: call mnemosyne_todo_list first, use permanent: true only when the human explicitly asks for outright deletion, and note the environment-dependent daemon behavior. It does not explicitly name an alternative tool such as mnemosyne_todo_add for the 'when not to use' case, so it stops just short of full exclusion guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.