List survey projects with coverage, year range, table counts, and access status. Distinguishes between readable, permission-restricted, and missing datasets to answer existence queries.
列出数据库里有哪些调查项目（CSES / DHS / HSES / LFS 等），带调查数量、覆盖国家、年份范围、表数和体积。会明确区分三种状态：已入库可读 / 数据在库但当前角色无权限 / 根本没入库——被问到某个调查有没有时，按这个区分如实回答。
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
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No arguments | |||
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 carries the full disclosure burden and does well: it reveals that results are permission-aware, distinguishing 'ingested and readable' from 'present but role lacks permission' from 'not ingested'. It does not mention cost, pagination, or latency, which keeps it short of a 5.
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 sentences, front-loaded with what is listed and what metadata accompanies each entry, followed by the permission/status nuance. The closing instruction to 'answer truthfully' is slightly prescriptive but earns its place by tying the three states to a concrete answering behavior.
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?
An output schema exists, so return-shape explanation is not strictly required, yet the description still summarizes the per-survey fields and adds the permission-state nuance an agent needs to answer existence questions without over-claiming. Nothing essential is missing for a zero-argument listing tool.
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 is nothing for the description to disambiguate, and it correctly spends no words on arguments.
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 and resource (list survey projects) and names concrete examples (CSES / DHS / HSES / LFS) that distinguish it from sibling listing tools like list_tables and list_schemas. It also enumerates the fields returned, so an agent knows exactly what this tool answers.
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?
Gives a clear trigger condition: when asked whether a particular survey exists, use this tool and answer according to the three-state distinction. It stops short of explicitly naming alternative tools (e.g., search_metadata) for other survey-discovery needs, so routing is implied rather than fully specified.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.