Skip to main content
Glama
Edlineas

AIVectorMemory

by Edlineas

task

Manage tasks across sessions: create, update, list, delete, or archive tasks. Updates sync with IDE tasks.md checkboxes and linked issue statuses.

Instructions

任务管理:batch_create/update/list/delete/archive。update 更新状态后自动同步所有 IDE 的 tasks.md checkbox,并联动同步关联问题状态。archive 将指定功能组的所有任务移入归档表。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tasksNo任务列表(batch_create)
titleNo任务标题(update 时可选修改)
actionYes
statusNo任务状态
task_idNo任务 ID(update/delete 时使用,即 list 返回的 task_id)
feature_idNo关联的功能标识(list/archive 时必填)
Behavior3/5

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

With no annotations, the description is the sole source of behavioral disclosure. It reveals significant side effects: update syncs all IDE tasks.md checkboxes and linked issue statuses; archive moves all tasks from a feature group to an archive table. However, it omits behaviors for delete (cascade/soft), batch_create (duplicate handling), and list (pagination/ordering), leaving gaps.

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 description is short (two sentences) and front-loads the actions, but the second sentence is dense with Chinese conditionals. It could be slightly more structured (e.g., bullet actions) but is efficient for its content.

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

Completeness2/5

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

Given the tool has 6 parameters, 5 actions, and missing output schema, the description lacks sufficient detail. It does not explain return values, error handling, or action-specific requirements beyond the brief mentions. The agent would need to infer or test behaviors for delete and batch_create.

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 coverage is high (83%), so the description adds limited param-specific value. It provides context for 'update' action (sync behavior) and 'archive' action (moves to archive table), but does not elaborate on the 'tasks' array structure or nesting of 'children' objects. Most param meaning is already conveyed by the schema.

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 clearly states the tool is for task management with explicit actions (batch_create, update, list, delete, archive). It distinguishes from sibling tools like auto_save, forget, graph, etc., as those do not overlap in function. However, it lacks a formal 'resource' identifier beyond '任务' and could be more explicit.

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?

The description outlines when to use each action (update syncs tasks.md, archive moves tasks), but does not provide explicit guidance on when to prefer this tool over others, nor does it mention prerequisites or when not to use it. Since siblings are unrelated, usage is somewhat implied but not formally guided.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Edlineas/aivectormemory'

If you have feedback or need assistance with the MCP directory API, please join our Discord server