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How many Japan Highly Skilled Professional (HSP / 高度専門職) points does this person have: 70, 80, or short?

japan_hsp_points_check
Read-onlyIdempotent

Scores the Japan Highly Skilled Professional points system (高度人材ポイント制 / 高度専門職 1号イ・ロ・ハ) from the MOJ ordinance (高度専門職省令, e-Gov 426M60000010037) and the ISA points table, rules as of 2026-10-30. category: academic (research / teaching, HSP i-a) | specialized (engineers, specialists, most employees, HSP i-b) | management (executives / owners, HSP i-c). Applies the official age bands (<30 / <35 / <40), salary-by-age table and the ¥3M floor (specialized / management below ¥3M cannot qualify at any points), education (doctor 30, MBA/MOT 25 for specialized/management, master 20, bachelor 10; +5 multiple fields), experience bands per category, research achievements, national qualifications (1 → 5, 2+ → 10; specialized), management position (representative 10, officer 5), and bonuses with their no-double-count rules (N2 not on top of a Japanese degree or N1; innovation support 10/20 with SME; SME R&D 3%; foreign qualification; growth-field project; designated top university; JICA; ¥100M investment and investment-management limits). Returns total, verdict (qualifies_80 | qualifies_70 | below_70 | below_salary_floor), summary, breakdown [{item, itemJa, points, basis}], pointsTo70/80, pr {route hsp80 (PR after 1 year at 80+) | hsp70 (3 years at 70+) | none}, hsp2 (HSP ii after 3 years), jSkip {eligible, rule} (Japan System for Special Highly Skilled Professionals: ¥20M+ with a master's or 10 years' experience, or ¥40M+ and 5 years' management), couldAdd (items not yet counted, sorted by points), warnings (e.g. age points dropping soon), pendingRevision, sources, disclaimer. Use for 'HSP points calculator', '高度人材ポイント 計算', 'do I have 70 points for HSP', 'highly skilled professional visa 80 points permanent residence 1 year', 'J-Skip eligibility'. Educational calculator, not immigration advice; not affiliated with ISA; ISA decides how each item is proved and counted.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "category": "<category>",
      "education": "<education>"
    },
    "name": "japan_hsp_points_check"
  }
}

Input Schema

NameRequiredDescriptionDefault
ageNoAge on the application date (academic / specialized). Or give birthDate.
smeNoEmployer is an SME (only adds with innovationSupport).
categoryYesacademic (HSP i-a: research / teaching) | specialized (HSP i-b: engineer, specialist, most employees) | management (HSP i-c: executive / business owner).
japaneseNon1 (JLPT N1 / BJT 480+ / Japanese major abroad, 15) | n2 (JLPT N2 / BJT 400+, 10) | none.
positionNoManagement: representative (代表取締役 etc.) | officer (取締役 / 執行役) | none.
birthDateNoYYYY-MM-DD, used with applicationDate when age is not given.
educationYesHighest degree: doctor | mba (MBA / MOT professional degree) | master (incl. other professional degrees) | bachelor | none.
annualSalaryNoExpected annual pay in Japan in yen incl. bonuses (e.g. 7500000). Give this or annualSalaryMan.
jicaTrainingNoCompleted JICA Innovative Asia training (5).
growthProjectNoMinistry-certified advanced project in a growth field (10).
researchItemsNoKinds of research achievement (patent, 3+ foreign-government grants, 3+ papers as corresponding author, other).
topUniversityNoDegree from a designated top university (10).
japaneseDegreeNoGraduated from a Japanese university or graduate course (10).
qualificationsNoSpecialized: related Japanese national qualifications / ISA-listed IT exams (1 → 5, 2+ → 10).
annualSalaryManNoSame, in 万円 (e.g. 750).
applicationDateNoYYYY-MM-DD (default: today in Japan).
experienceYearsNoYears of relevant experience (research/teaching, the job's field, or business management).
localGovSupportNoEmployer gets local-government support for hiring highly skilled foreigners (10).
multipleDegreesNoDoctor / master / professional degrees in two or more fields (+5).
smeResearch3pctNoSME employer with R&D over 3% of revenue (5).
innovationSupportNoEmployer receives a listed innovation-support measure (10; 20 with sme).
foreignQualificationNoWork-related foreign qualification / award (5).
investmentManagementNoSpecialized / management: investment-management work (10).
personalInvestment100mNoManagement: invests ¥100M+ in the business (5).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already certify read-only, idempotent, closed-world, non-destructive, so the description's burden is lighter — yet it still adds rule-version dating (as of 2026-10-30), the exact verdict vocabulary, the derived PR routes, and a scope disclaimer that it is educational and not immigration advice. It also discloses pendingRevision and warnings, which the agent would otherwise not anticipate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

The purpose and category definitions are front-loaded and earn their space, but the remainder is a single dense wall of text enumerating nearly every scored item and return field. It is information-rich rather than padded, yet the lack of structure makes it harder to scan than it needs to be.

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?

With 24 parameters, four enums, no output schema, and a rule-driven domain, the description supplies what is missing elsewhere: the return shape (total, verdict, breakdown, pointsTo70/80, pr, hsp2, jSkip, couldAdd, warnings), the legal sources, and the version date. An agent has enough to call this correctly and to interpret the result.

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%, so the baseline is 3; the description earns more by adding scoring semantics the schema does not carry, notably the no-double-count rules (N2 not stacked on a Japanese degree or N1) and the ¥3M salary floor for specialized/management. Age bands and bonus interactions are likewise spelled out at the rule level rather than as parameter descriptions.

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 opening states a specific verb and resource (scores the Japan HSP points system, citing the MOJ ordinance and ISA table) and immediately distinguishes the three categories it handles. An agent can tell this apart from siblings like japan_permanent_residency_check or japan_visa_fee_check 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.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The closing 'Use for' block lists concrete trigger phrasings in both English and Japanese, covering the calculator, the 70-point question, the 80-point/1-year PR scenario, and J-Skip. It does not explicitly say when NOT to use this versus japan_permanent_residency_check, which is the one clear gap.

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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