Retrieve AI work details by agent, workflow, or weekly trends, covering tasks, tokens, duration, cost, and human intervention. Optionally include evolution metrics.
按 Agent / Workflow / 周趋势查询 AI 工作明细（任务/token/耗时/成本/人工介入），可附带进化四维趋势。
| Name | Required | Description | Default |
|---|---|---|---|
| agentId | No | 按 Agent 过滤（缺省全量） | |
| evolution | No | 附带进化四维趋势 | |
| workflowId | No | 按 Workflow 过滤（缺省全量） | |
| weeklyTrend | No | 附带周趋势（活跃度/成功率/成本） |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It implies a read-only query but never states it explicitly, nor does it mention permissions, side effects, or response format. It only says 'query' which hints at non-destructive behavior, but this is not made explicit. There is no coverage of rate limits, pagination, or aggregation behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single concise sentence that front-loads the core purpose (query AI work details) and then lists optional dimensions. No wasted words, all information is relevant. This is an efficient and well-structured description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description carries the full burden of explaining the tool's behavior. It lists the fields returned, but does not describe the response format, whether results are aggregated or per-item, or any pagination/limits. For a query tool with no output schema, this is a significant gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds some context by listing the fields (tasks/tokens/time/cost/human intervention) that the query returns, which gives meaning beyond parameter names. However, it does not provide format or syntax details beyond what the schema already defines, so it stays at baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool queries AI work details (tasks/tokens/time/cost/human intervention) with optional filters by Agent, Workflow, and weekly trend, plus an optional evolution trend. It uses a specific verb and resource, and distinguishes itself from sibling cost_query by covering broader metrics. However, it does not explicitly name sibling alternatives, so it loses a point for differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like cost_query or stats. The description implies it is for querying work details, but there is no mention of when to prefer it or when not to use it. This leaves the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.