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Glama

独行录 / opcmenu

by io.github.yzlee

列 OPC 园区

list_parks
Read-onlyIdempotent

浏览 / 筛选 OPC 园区目录（六城）。

【杀手用法】按补贴类型筛：benefitType=RENT_SUBSIDY 找「有租金补贴的园区」——这是主理人/找资源者最高频的诉求。可叠加 city / track / 状态 / 关键词。

【drill-down】get_park 看补贴明细 + 入驻条件 + 信源。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNo关键词，命中名称 / 运营方 / 区域
cityNo城市，如 北京/上海/深圳/杭州/广州/成都
limitNo返回条数，默认 20
trackNo赛道标签过滤，如 新消费/AI
cursorNo分页游标
statusNoOPERATING 已运营 | PLANNED 规划中
benefitTypeNo只看含某类补贴的园区：RENT_FREE（免租） | RENT_SUBSIDY（租金补贴） | COMPUTE_VOUCHER（算力券） | MODEL_VOUCHER（模型券） | STARTUP_FUND（创业资金） | SETTLEMENT（落户） | FUND（产业基金） | ORDER（订单导入） | TALENT_HOUSING（人才公寓） | LOAN（创业贷款） | OTHER（其他）

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already cover readOnlyHint, idempotentHint, and destructiveHint=false. The description adds useful behavioral context: the tool covers a six-city OPC directory, and detail-level data such as subsidy breakdowns and entry conditions is intentionally delegated to get_park. No contradiction with annotations.

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?

The description is compact and well-structured: purpose statement, killer use case, and drill-down pointer. Every sentence earns its place, and the most important operational guidance is front-loaded.

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?

The schema documents all 7 optional parameters with Chinese labels and enum meanings, annotations cover the safety profile, and the description completes the picture with usage intent and the get_park drill-down. For a simple list/filter tool, nothing essential is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description goes further by teaching combinability of filters ('可叠加 city / track / 状态 / 关键词') and by highlighting the RENT_SUBSIDY enum value as the most important use case.

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 opens with '浏览 / 筛选 OPC 园区目录（六城）', giving a specific verb, resource, and scope. It also differentiates from the get_park drill-down sibling, so an agent can tell catalog browsing from detail lookup without opening the schema.

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?

It explicitly presents the highest-frequency use case: benefitType=RENT_SUBSIDY to find parks with rent subsidies, and states that city / track / status / keyword can be stacked. It also gives the alternative route: get_park for subsidy details, entry conditions, and sources.

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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TDQS

A4.1/5.0
Disambiguation4/5

Each tool has a clearly documented purpose, often with explicit 'when to use' guidance and cross-references, making the vast majority easy to tell apart. A few clusters (get_my_brief, get_my_positioning, get_my_work, get_my_dispatch) and data-overlapping get_my_card vs get_my_profile require careful reading, but descriptions are detailed enough to prevent serious misselection.

Naming Consistency4/5

The overwhelming majority follow snake_case verb_noun conventions (create_product, update_need, list_my_signups). Minor deviations include noun-only feed names (personalized_feed, random_feed), inconsistency between 'prefs' and 'preferences' in notification tools, and a mix of update_* and set_* for mutations, but the pattern remains predictable overall.

Tool Count1/5

137 tools is an extreme mismatch for any MCP server, far exceeding the 50+ threshold for a score of 1. Even with a broad multi-domain platform, this volume makes tool selection and navigation impractical and heavily burdens the agent's context window.

Completeness5/5

The surface covers full lifecycles for needs, products, activities/signups, conversations, collaboration goals/tasks, dispatch, profile/onboarding, and supporting resources like companies, parks, policies, and ratings. Deliberate omissions (no user-post creation, no organizer profile editing via agent) are explicitly documented, so core workflows have no obvious dead ends.

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