data_infoCheck where your job-search data is stored, whether each file exists and its approximate record count, and review the local privacy policy before switching devices.
查看求职数据保存在哪里、各文件是否已生成与大致条数，并说明隐私策略。换机前可先看这里。
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. '查看' implies a read-only, non-mutating operation and the description discloses what information is surfaced (location, generation status, counts, privacy policy), which is helpful. It does not explicitly confirm read-only safety or whether it touches/moves data, so it is adequate but not rich.
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?
Two tightly packed sentences: the first enumerates the outputs, the second gives the usage cue. Front-loaded and every clause earns its place with no filler.
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?
No output schema exists, so the description must describe returns – and it does (where data lives, whether files are generated, approximate counts, privacy policy). For a zero-param informational tool this is close to complete, though it doesn't clarify the response structure or freshness of the counts.
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?
The tool takes zero parameters, so the baseline is 4. There are no parameter semantics to clarify, and the description correctly implies no input is needed.
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?
States a specific verb (查看) and concrete resources: data storage location, per-file generation status, record counts, and privacy policy. This is clearly distinguishable from siblings like data_export or jobok_workflow, which do different things.
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?
Adds one usage context ('换机前可先看这里' – check here before switching machines), which implies a pre-migration scenario. However, it never names when NOT to use it or points to an alternative (e.g., data_export for actually extracting data), leaving the choice to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.