Find New Zealand doctors and GP practices by condition, procedure or place, with sources. No signup.
Scored across 6 tools
Each tool has a clearly distinct role: metadata (about_database), enumeration (list_specialties), search (search_doctors, search_gp_practices), detail (get_doctor), and reference data (public_waitlist). search_doctors and search_gp_practices target related but distinct entity types (doctors vs practices) and the descriptions distinguish them well, though a rushed agent could momentarily conflate the two.
Four of six tools follow a clean verb_noun pattern (get_doctor, list_specialties, search_doctors, search_gp_practices). The remaining two (about_database, public_waitlist) deviate slightly by not being verb-led, but the set is still highly readable and predictable.
Six tools is well-scoped for a doctor-finding directory: search, detail, enumeration, reference data, and metadata each earn their place with no redundant or filler tools.
The surface covers the core workflow well—discover specialties, search doctors and GP practices, fetch detailed evidence, and check public waitlists. Coverage is strong for a directory, with only minor gaps such as no explicit comparison or booking tool, which agents can work around.
Sources, read dates, coverage counts and known gaps. Free.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered structurally. The description adds genuine behavioral value by disclosing 'Free' (no cost/credit consumption) and that the data has 'known gaps' — a limitation the agent should know before trusting results. It stops short of describing response shape or freshness semantics, so 3 is appropriate.
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?
A single telegraphic fragment with no filler; the most useful facts (what it returns, that it's free) are front-loaded. It is arguably too clipped — a verb would cost nothing — but nothing is wasted.
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?
With no parameters and no output schema, the description effectively serves as the return-value summary (sources, read dates, coverage counts, gaps), which is the key thing an agent needs. A note on when to consult it would make it complete.
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 there is nothing for the description to disambiguate; the baseline for a 0-param tool is 4.
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?
The description names the specific content the tool returns — sources, read dates, coverage counts, known gaps — which is a precise purpose for a metadata tool. It lacks an explicit verb ('Returns...'), but an agent can tell this is the database provenance/coverage endpoint and distinguish it from the doctor-search siblings.
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?
There is no when-to-use guidance, no mention of alternatives, and no stated precondition such as 'call this before search_doctors to learn coverage.' The closest signal is 'known gaps' and 'Free', which imply pre-query inspection and no billing cost, but that is inference rather than instruction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Evidence for New Zealand doctors from search_doctors: pass doctor_ids (up to 10 at once) or one doctor_id. Each different doctor you open counts toward a daily limit for your connection (replies show daily_doctor_limit when it matters); opening a doctor again the same day is free. Open the doctors you are seriously considering, not every result. Each doctor: specialties, title, qualifications, focus areas and subspecialties they list, further training, languages, whether their services see children; every private and public service with clinic addresses, phone numbers and websites, procedures and conditions the service lists, fee categories and fee lines, ages, hours, how to get referred, and whether it says Southern Cross Affiliated Provider or nib First Choice (insurer_notes also says whether the doctor's own page says so); the Medical Council register entry (status, scope of practice, conditions, qualifications, practising certificate); experience (each vocational scope with the date it was granted and years since, first New Zealand registration, primary medical degree year, New Zealand honours with citation, University of Auckland title and hospital appointments, approximate count of papers with a New Zealand affiliation and a link to the list); hospital website links; and source links with read dates. For a GP, services include the practice's enrolment status and fee table. Profiles are not reproduced: give the person the Healthpoint link (sources.healthpoint) for the doctor's own words.
| Name | Required | Description | Default |
|---|---|---|---|
| doctor_id | No | One doctor_id from search_doctors, e.g. 'nz_4k9m2x7qph3t'. | |
| doctor_ids | No | Up to 10 doctor_ids from search_doctors, e.g. ['nz_4k9m2x7qph3t', 'nz_8w2c5n1kd7ra']. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld=false), and the description adds substantial non-obvious behavior: a per-connection daily limit, that replies surface daily_doctor_limit when relevant, that re-opening the same doctor the same day is free, and that profile text is not reproduced (use sources.healthpoint instead). That is exactly the kind of quota/rights context annotations cannot convey.
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?
The first sentence is well front-loaded, but the return-value enumeration is a single ~120-word run-on sentence listing dozens of fields with semicolons. Because there is no output schema that content is load-bearing, yet it would be far more usable as a structured list, so it reads as exhaustive rather than concise.
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?
With no output schema, the description carries the return-value burden and does so thoroughly, and it covers quota mechanics and the copyright/attribution constraint. What is missing is failure behavior (invalid or unknown IDs, what happens if more than 10 are passed) and any hint of the response's shape.
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 coverage is 100%, so baseline is 3; the description adds real value by framing the two parameters as alternatives ('pass doctor_ids (up to 10 at once) or one doctor_id') rather than merely restating the schema, and it ties the batch size to the quota cost. It does not explain behavior when both are supplied or when the cap is exceeded.
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: opens the full evidence profile for a New Zealand doctor identified by doctor_id(s) obtained from search_doctors. It is immediately distinguishable from sibling search_doctors (discovery) and list_specialties (browsing), and the 'Each doctor: ...' enumeration makes the scope of retrieval unambiguous.
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 clear context ('from search_doctors') and an explicit when-not ('Open the doctors you are seriously considering, not every result'), plus the batching affordance. It stops short of a fully explicit routing rule (e.g. 'use search_doctors to find IDs, do not call this to search'), but the workflow is easy to infer.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Specialty names used in this database (Healthpoint categories) with doctor counts. Free.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so safety behavior is covered. The description adds two things beyond that: the return content (specialty names plus doctor counts) and the fact that calls are free. It does not describe ordering, pagination or result size, so it is useful 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?
A single front-loaded sentence that carries the resource, scope and payload, followed by a one-word cost note. Nothing is wasted, though the 'Free.' fragment is slightly clipped in style.
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?
For a zero-parameter, read-only list tool with strong annotations and no output schema, the description tells the agent what it returns (names and doctor counts) and that it is free. Ordering and result size are the only notable omissions.
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 there is nothing for the description to clarify; the schema coverage is 100% and the baseline for a parameterless tool applies.
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?
Names the resource (specialty names) and the scope (used in this database / Healthpoint categories) and adds the payload detail 'with doctor counts'. No verb is stated, relying on the tool name for the action, but it is still clearly distinguishable from siblings like search_doctors or get_doctor.
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?
'Free.' signals zero cost, which is a weak usage cue, but there is no statement of when to call this rather than search_doctors or about_database, and no prerequisites or exclusions are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Public-system waiting lists from Health NZ by district and specialty (latest month and the same month a year earlier): people waiting for a first specialist assessment (FSA) and for planned treatment (surgery), and the share waiting over 120 days. Use it when the person is weighing public against private, or which district is faster. Give specialty and/or district. Free.
| Name | Required | Description | Default |
|---|---|---|---|
| district | No | Health NZ district, e.g. 'Auckland', 'Canterbury', 'Capital and Coast'. Part of a name also matches (Canterbury includes South Canterbury); a city or region is read as its district (Wellington → Capital and Coast, Dunedin → Southern), shown in district_read_as. | |
| specialty | No | e.g. 'Orthopaedic', 'ENT', 'General Surgery', 'eye'. An exact name is matched first, then names containing each word, then the same without words like 'surgery' and with common plain words mapped (eye → Ophthalmology, heart surgery → Cardiothoracic, cardiologist → Cardiology, internal medicine → General Medicine), then part of a name; both of Health NZ's names for the same specialty are returned (e.g. Orthopaedics and Orthopaedic Surgery). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile (readOnly, idempotent, non-destructive, not open-world), and the description adds genuinely new context: the reporting window (latest month plus same month a year earlier), the exact measures returned, and that it is free to use. It does not discuss pagination or response shape, but for a read-only public dataset that is a minor omission.
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?
Front-loaded with the data content, then the usage trigger, then the minimal call instruction and cost note — every clause carries information. The tail ('Give specialty and/or district. Free.') is slightly clipped but not wasteful.
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, but the description compensates by stating exactly which measures and which time periods come back, and the schema thoroughly documents both optional filters. An agent has what it needs to decide and invoke; only return formatting/pagination remains unstated.
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 coverage is 100%, so the two parameters' matching, stemming and alias behavior is already fully documented in the schema. The description only adds that both are optional and combinable ('Give specialty and/or district'), which is a valid but marginal addition over the structured data, so the baseline 3 applies.
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?
The description names the exact resource (Health NZ public-system waiting lists) and enumerates the metrics returned: people waiting for a first specialist assessment, for planned treatment, and the share waiting over 120 days, plus the two-month time window. It is unmistakably distinct from the doctor/practice siblings, though it never names or contrasts them explicitly.
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?
'Use it when the person is weighing public against private, or which district is faster' gives a concrete situation that selects this tool, and 'Give specialty and/or district' tells the agent how to scope the call. No explicit exclusions or named alternatives against the sibling tools, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Free short list of New Zealand doctors for a need; use it first whenever the person needs a doctor or specialist in New Zealand. Give at least one of need, specialty, place or name. need = a condition, procedure or focus in plain English (e.g. 'ACL reconstruction', 'endometriosis', 'skin cancer', 'cataract surgery'); it is matched against the focus areas doctors list first, then the procedures their services list, their specialty, and their own profile text (not shown here). specialty = a name from list_specialties, a word from one (e.g. 'orthopaedic', 'ENT') or a plain word (e.g. 'eye', 'skin', 'heart'); matched word by word (word endings may differ, e.g. 'cardiologist', 'paediatrician'; not fragments inside words), and the reply's specialty_read_as lists the specialty names used. place = a New Zealand city, suburb, or region or Health NZ district (e.g. 'Christchurch', 'North Shore', 'Hawke's Bay', 'Hutt Valley'); when a town search leaves out doctors listed only on the wider region's page or in its other towns, place_note says how many and which place to use instead. Each result: doctor_id, name, specialties, vocational scope, cities, sectors (private, public), match_basis (with a need: stated_focus, services_listed (the doctor's own or a small practice's service page), shared_service_listed (a hospital department or large group page they are linked to, so not necessarily done by this doctor), specialty, specialty_for_symptom (the need is a symptom few doctors list, and their specialty usually sees it; need_note says which specialties), profile_text or partial), place_match (with a place: city_or_address, city_in_region, address_contains or region_page_only), warnings (e.g. not practising on the Medical Council register), specialist_since (year first on the Medical Council vocational, i.e. specialist, register in New Zealand), recognition (New Zealand honours, University of Auckland title), listing (medical_council_register_only when the doctor has no clinic listing here), possibly_same_person_as (another entry with the same name that may be the same doctor) and detail_has (what get_doctor adds). General practitioners are left out unless specialty is general practice (e.g. 'GP') or a name is given; to find a GP clinic use search_gp_practices. Doctors only on the register are included when practising with a specialist scope (any status with a name). Results are ranked first by how directly the doctor's own listing matches the need (doctors who list all its words; then, when the need is a symptom such as back pain, doctors whose specialty usually sees it; then doctors who list some of the words; then words only in profile text), then by place_match (with a place); with experienced_first, longer as a specialist next. Doctors known only from the Medical Council register (no clinic listing) come after all others. Not ranked by quality or outcomes. Then call get_doctor with the doctor_ids you are considering. Up to 10 results per search and paging stops at 30: narrow the need or the place instead of paging.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Doctor's name or part of it, to check a named doctor. | |
| need | No | Condition, procedure or focus, plain English. | |
| child | No | True when the patient is a child: among doctors in the same place who match the need equally well, those in paediatrics or who list children in their focus come first, then those whose services say they see children; doctors whose services list only adult ages are left out. Most listings do not say, so those doctors stay in. | |
| limit | No | Default 10. | |
| place | No | New Zealand city, suburb, or region or Health NZ district (e.g. 'Waikato', 'Hawke's Bay', 'Capital and Coast'). | |
| gender | No | Only when the person asks. Gender is recorded for only a small share of doctors (when their Healthpoint page states it); doctors without it are left out and gender_note says how many. | |
| offset | No | For paging (at most 20, so 30 results in all: narrow the search instead). | |
| sector | No | private = the doctor lists a private service; public = a public (Health NZ) service. Default any. | |
| language | No | Language other than English the doctor, or a small clinic (3 doctors or fewer) they work in, lists, e.g. 'Mandarin', 'Hindi', 'Samoan'. | |
| specialty | No | Specialty name, a word from one, or a plain word like 'eye' (see list_specialties). | |
| experienced_first | No | True when the person wants an experienced or senior doctor: among doctors who match equally well, those longer on the New Zealand specialist (vocational) register come first. Time on the register is not quality, and doctors who trained overseas may have practised longer than it shows. | |
| southern_cross_affiliated | No | True keeps doctors whose own Healthpoint page or at least one of whose service pages says Southern Cross Affiliated Provider (cover still depends on the policy and often prior approval; confirm). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile (readOnlyHint, idempotent, non-destructive), but the description goes well beyond them: the ranking order, the match_basis taxonomy, the 10-per-search / 30-result paging cap, the caveat that results are "Not ranked by quality or outcomes", register-only doctors sorting last, and explicit warnings about Southern Cross cover and the Medical Council register.
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?
Front-loaded with purpose and dense with genuinely useful content, but it is a single ~450-word paragraph with no headings or bullets, and sections such as the child, gender, and experienced_first behavior mostly restate the schema. Efficient per sentence, poorly structured overall.
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 fully by enumerating every returned field (doctor_id, match_basis, place_match, warnings, specialist_since, listing, possibly_same_person_as, detail_has) and by documenting filter side-effects like gender_note and place_note. Nothing an agent needs to call or interpret it is missing.
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 coverage is already 100% with detailed per-parameter text, so the baseline is 3, but the description adds real meaning: how "need" is matched (focus areas, then service procedures, then specialty, then profile text), how "specialty" matches word-by-word, and what place_note / gender_note signal when a filter prunes results. The child/experienced_first wording largely restates the schema, so it stops short of a 5.
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 ("short list of New Zealand doctors") and scopes it to a need, then explicitly positions itself against siblings: GPs are excluded and search_gp_practices is named for that case. An agent can distinguish it from search_gp_practices and get_doctor without opening a schema.
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 explicit when-to-use ("use it first whenever the person needs a doctor or specialist in New Zealand"), when-not ("General practitioners are left out unless specialty is general practice"), the named alternative for the excluded case, and the follow-up step ("Then call get_doctor with the doctor_ids you are considering").
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Free list of New Zealand general practices (GP clinics), or urgent care clinics, near a place, from Healthpoint. Use it when the person needs a GP, wants to enrol with a practice, or needs urgent but not emergency care. Each practice: whether it says it is enrolling new patients (yes; restricted = only some people, e.g. family of patients or people living nearby; no; does not apply = urgent care that does not enrol; unknown = the page does not say), the practice's own enrolment note, its fee table (the first fee table on its page, usually fees for enrolled patients by age, without and with a Community Services Card; with age, the row for that age), addresses, phone numbers, website, online booking link, languages, hours, the doctors listed there (doctor_ids for get_doctor) and the date Healthpoint says the page was last updated. In New Zealand most people enrol with one general practice: visits cost less once enrolled, and a GP referral is the usual way to a public specialist. Give place or name. Practices are not doctors, so this does not count toward the daily doctor limit. Enrolment and fees change often: tell the person to phone the practice to confirm.
| Name | Required | Description | Default |
|---|---|---|---|
| age | No | The patient's age: each result then shows the fee row for that age. | |
| kind | No | gp = general practices (default; also nurse-led, online, student and rest-home practices, named so in each result's kind); urgent_care = accident and urgent medical care and after-hours clinics (no enrolment needed); any = both. | |
| name | No | Practice name or part of it, to check a named practice. | |
| limit | No | Default 10. | |
| place | No | New Zealand city, suburb or region (e.g. 'Papanui', 'Hamilton', 'North Shore', 'Canterbury'). | |
| offset | No | For paging (at most 40). | |
| language | No | Language other than English the practice lists, e.g. 'Mandarin', 'Samoan', 'te reo Maori'. | |
| enrolling | No | yes = only practices that say they are enrolling new patients; yes_or_restricted also keeps practices enrolling only some people (read enrolling_note). Default any (enrolling practices come first). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover safety (readOnly, idempotent, non-destructive, closed-world), but the description adds meaningfully more: the daily doctor limit exemption, the enrolment-status vocabulary (yes/restricted/no/does not apply/unknown), which fee table is returned, and the operational advice that enrolment/fees change often and the person should phone to confirm. That is real behavioral context beyond the structured fields.
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?
Front-loaded with the core purpose and triggering situations, and every part is generally useful given there is no output schema. However the long run-on 'Each practice: ...' enumeration is dense and could be more scannable.
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?
With no output schema, the description carries the full return-value burden and does so thoroughly (enrolment status, enrolment note, fee table, contact fields, hours, languages, doctor_ids, last-updated date). It also supplies the domain model (enrolment lowers cost, GP referral is the usual path to public specialists) needed to interpret results correctly.
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%, so the schema already documents all 8 parameters including both enums. The description largely restates schema content (kind subtypes, enrolment meaning, age->fee row) rather than adding new parameter interpretation, so the baseline 3 applies.
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?
Specific verb+resource (find/list New Zealand general practices, or urgent care clinics, near a place, from Healthpoint), plus the scope is narrowed against siblings by noting 'Practices are not doctors, so this does not count toward the daily doctor limit' and pointing to get_doctor for doctor_ids. An agent can distinguish this from search_doctors/get_doctor without opening any schema.
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?
Names concrete triggering situations: 'when the person needs a GP, wants to enrol with a practice, or needs urgent but not emergency care.' It also routes to get_doctor (doctor_ids) and clarifies the doctor-vs-practice boundary. There is no explicit 'when not to use' other than that boundary, so it stops just short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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