Skip to main content
Glama

search_nhi_wiki

Read-onlyIdempotent

Search Taiwan's NHI knowledge base for natural-language background questions on audit, drugs, fees, plans, services, insurance, forms, records, and admin. Returns ranked excerpts with source URLs.

Instructions

Search across Taiwan's official NHI knowledge base (健保署全球資訊網) for natural-language background questions. Covers 9 categories: audit (審查 — review rules / rejection grounds), drugs (藥品特材 — formulary, payment limits), fees (費用 — copay, premiums, contribution), plans (醫療計畫 — disease-management programs), services (醫療服務 — covered benefits), insurance (投保 — enrollment), forms (表單 — applications), records (紀錄 — documentation rules), admin (行政 — contracting, accreditation). Returns up to 10 ranked excerpts (most relevant first); each result includes title, content snippet, source URL, and category tag. Returns an empty list (not an error) when the query has no matches. Use when an agent needs broad NHI policy background not tied to a specific code — e.g. '慢性病連續處方箋天數上限' / 'how does balance billing work for orthodontics' / 'what are the rules for telemedicine reimbursement'. Typical follow-up: when an excerpt mentions a specific code (e.g. '0317A', '00101B'), call the appropriate code-specific tool (lookup_rejection_code, lookup_fee_code) for the canonical entry. Don't use when you already know a specific rejection code, procedure code, drug name, or audit-clause topic — those have dedicated tools that return structured fields rather than excerpts. Reference only — official 健保署 publications are authoritative; ranked excerpts may lag the latest revision and the snippet is not the full document. Curated by OPDSTAR (https://opdstar.com).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesRequired. Natural-language query in Traditional Chinese or English. Multi-word phrases work best (concept + qualifier). Examples: "慢性病連續處方箋天數上限" / "急診轉診費用" / "telemedicine reimbursement rules" / "orthodontic balance billing". Single Chinese characters or 1-letter strings are unlikely to return useful matches.
categoryNoOptional. Narrows the search to one category. Use `audit` for review/rejection rules, `drugs` for formulary/payment limits, `fees` for copay/premiums, `plans` for disease-management programs, `services` for covered benefits, `insurance` for enrollment, `forms` for applications, `records` for documentation rules, `admin` for contracting/accreditation. Omit to search all categories (recommended when the topic is unclear).
limitNoOptional. Maximum number of ranked excerpts to return. Range 1-10. Default 5. Increase to 10 when surveying a topic; keep at 5 for targeted look-ups to save context.
Behavior5/5

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

Annotations provide readOnlyHint and idempotentHint, but the description adds significant context: returns empty list for no matches (not error), results are ranked excerpts that may lag revisions, and it's reference only. 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is detailed but well-structured with bullet lists and bold for emphasis. It front-loads key information and uses separate sections for usage and limitations. While lengthy, every sentence adds value.

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?

Given the tool's complexity (multiple categories, output format, usage context), the description is very complete. It covers what happens on no match, provides follow-up suggestions, warns about content staleness, and cites authority. No output schema exists, but the description adequately explains return values.

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 coverage is 100%, but the description adds valuable details: example queries for 'query', category explanations, and limit usage guidance (e.g., 'survey' vs. 'targeted'). This goes beyond what the schema provides.

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 clearly states the tool searches Taiwan's NHI knowledge base for natural-language background questions, lists 9 categories, and describes output. It distinguishes from sibling tools like lookup_rejection_code and lookup_fee_code by specifying when to use this broad search versus code-specific tools.

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?

Explicitly says when to use (broad NHI policy background not tied to a specific code) and when not to use (when a specific code or topic is known). Provides typical follow-up actions, making it easy for the agent to decide.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/tatsuju/opdstar-nhi-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server