机构/大V评分排行(当前)
get_agency_ranking机构/大V评分排行(当前)。按 agency_id 返回机构/大V分(约 450~1500,1000 左右算中等)、有效样本数、胜率等。(每次调用计费 1 次)
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | 返回条数,默认 50,最大 500 | |
| order | No | 排序字段 | score |
| offset | No | 分页偏移 | |
| min_score | No | 最低机构/大V分 |
get_agency_ranking机构/大V评分排行(当前)。按 agency_id 返回机构/大V分(约 450~1500,1000 左右算中等)、有效样本数、胜率等。(每次调用计费 1 次)
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | 返回条数,默认 50,最大 500 | |
| order | No | 排序字段 | score |
| offset | No | 分页偏移 | |
| min_score | No | 最低机构/大V分 |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent and closed-world, so the description sensibly focuses on what they can't say: it discloses the per-call billing cost (每次调用计费 1 次) and explains that scores cluster roughly 450–1500 with ~1000 as middling. That score-scale context is genuinely needed to interpret results and is not derivable from any structured field.
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 dense sentences with the resource and scope front-loaded, then the returned fields, then the cost caveat last. No filler, though the repeated '机构/大V评分排行(当前)' opening partially restates the title.
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?
There is no output schema, and the description compensates by enumerating the key returned fields (agency_id, score, n_eff, win_rate). What's missing is minor: whether a total count is returned for paging, and the unit/meaning of n_eff and win_rate.
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 description coverage is 100% — limit, offset, order (with enum) and min_score are all documented in the schema, so the baseline applies. The description's score-range context does help an agent choose a sensible min_score, but it adds no syntax or format guidance for the parameters themselves.
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+resource — ranking of agency/KOL scores — and the '(当前)' qualifier implicitly separates it from get_agency_history and get_agency_pit. It also names the fields returned (score, effective sample count, win rate), so an agent knows exactly what it retrieves, though it never names the sibling tools directly.
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?
Usage is only implied: '当前' suggests this is the live/snapshot view as opposed to the historical siblings, but there is no explicit 'use this when...' or 'use get_agency_history instead when...' statement. The billing note signals a cost trade-off but gives no guidance on when that cost is worth paying.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.