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aida_task_start

Start tracking a new development task or feature implementation to capture structured coding session data for AI development observability.

Instructions

当你开始一个新任务或功能开发时调用。在接到用户需求、开始编码前调用。每个任务的完整数据采集流程:1) aida_task_start 2) 编码 3) aida_log_files 4) aida_log_review 5) aida_task_done。多个子任务必须每个都单独 start/done。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYes任务标题,简洁描述要做什么
stageNo所属模块或阶段,如 Authentication, UI, API 等

Implementation Reference

  • Handler function for aida_task_start which initializes a task item and updates the state.
    function handleTaskStart(args: any): any {
      const { path, data } = ensureRunJson();
      const id = nextId(data.tasks, 'TASK');
      const task: TaskItem = {
        taskId: id,
        title: args.title,
        status: 'in-progress',
        stageName: args.stage || 'default',
        prdPhase: '',
        acceptance: '',
        createdAt: now(),
        startedAt: now(),
        completedAt: null,
      };
      data.tasks.push(task);
      data.summary.totalTasks = data.tasks.length;
      data.context.currentTaskId = id;
      addEvent(data, 'task_created', { taskId: id });
      addEvent(data, 'task_started', { taskId: id });
      addTimeline(data, 'task', `${id}: ${args.title}`);
      save(path, data);
  • Tool registration/routing for aida_task_start within the MCP server's message handler.
    case 'aida_task_start':
      result = handleTaskStart(args);
      break;
Behavior4/5

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

With no annotations provided, the description carries the full burden. It successfully discloses the workflow context ('数据采集流程' - data collection process) and lifecycle implications, but lacks explicit detail about return values, idempotency, or specific side effects (e.g., whether it creates a persistent record).

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?

Four sentences with zero waste: (1) purpose definition, (2) timing context, (3) workflow sequence, (4) subtask rule. Logical front-loaded structure moves from general use to specific sequencing constraints.

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?

Given the workflow complexity and sibling tool ecosystem, the description successfully explains the complete task lifecycle, integration with logging tools, and subtask protocols. No output schema exists, and none is required given the schema coverage.

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 100% with both 'title' and 'stage' fully documented in the schema including examples. The description adds no parameter details, which is acceptable when the schema is self-documenting, warranting the baseline score of 3.

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 clearly states the tool '开始一个新任务' (starts a new task) with specific verb+resource, and distinguishes from siblings by positioning it as step 1 of a 5-step workflow (contrasting with aida_task_done at step 5 and the aida_log_* middle steps).

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

Usage Guidelines5/5

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

Provides explicit temporal guidance ('在接到用户需求、开始编码前调用' - call after requirements, before coding), sequences the full workflow with numbered steps, and specifies subtask handling rules ('多个子任务必须每个都单独 start/done'), clearly delineating when to use vs. alternatives.

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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