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threat_model_starter

Creates a tailored threat-modeling starting point from a system description, returning prioritized risk matrices, trust-boundary guidance, and missing input details to review with security teams.

Instructions

対象システムの説明から公開範囲・扱うデータの機微性・利用者規模・主体の種類を読み取り、その状況に合わせた脅威モデリングの出発点を作る。読み取り結果と根拠、状況に応じた信頼境界の引き方、資産 × 6 観点(なりすまし/改ざん/否認/情報漏えい/サービス妨害/権限昇格)の優先度入りの表(空欄では返さない)、まず埋めるべき 3 セル、観点ごとにこの状況で実際に起きやすいこと、入力に足りない情報を返す。社外公開の大規模ポータルと閉域網の IoT 基盤では中身が変わる。出力は草案であり、セキュリティ担当との対話で確定させる前提。 / Read exposure, data sensitivity, user scale, and subject types out of a system description, then build a threat-modelling starting point fitted to that situation. Returns what was read and on what evidence, situation-specific trust-boundary rules, an asset-by-lens matrix over the six lenses (spoofing, tampering, repudiation, information disclosure, denial of service, elevation of privilege) that comes back already prioritized rather than blank, the three cells to fill first, what actually tends to go wrong here under each lens, and what the input did not say. A large public portal and an isolated IoT platform get materially different answers. The output is a draft to be settled in conversation with a security owner.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNo出力言語 / Output languageboth
actorsNo登場する主体・攻撃者。省略すると一般的な候補を出す / Subjects and adversaries; omitted, a generic candidate set is used
assetsNo守る対象。省略すると一般的な候補を出す / What is being protected; omitted, a generic candidate set is used
systemNo対象システムの説明。公開範囲・利用者規模・扱うデータ・外部連携が書かれているほど助言が具体的になる。省略すると書き方の案内を返す / A description of the target system. The more it says about exposure, user scale, the data held, and external connections, the more specific the advice. Omit it to get guidance on what to write — 最大 20,000 文字 at most 20,000 characters
Install Server

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations provided, the description carries the full behavioral burden and does so richly. It discloses that the matrix is filled and prioritized rather than blank, that it returns evidence-based inferences, the three cells to fill first, likely attack realities per lens, missing input information, and that the output is explicitly a draft to be settled with a security owner.

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 long but every sentence earns its place: purpose, output contents, situation-dependent behavior, and draft status are all packed densely and the main outcome is front-loaded. The bilingual repetition is justified by the tool's own language parameter and is not filler.

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?

For a complex generative/analysis tool with no output schema and no annotations, the description is unusually complete. It specifies what is returned, what is not returned (blank cells), how it varies by context, what it will flag as missing input, and the status of the output.

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

Parameters3/5

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 schema already documents lang, actors, assets, and system well. The description reinforces the value of a detailed system description and mentions the omitted-system fallback, but adds little parameter-specific meaning 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 states a specific verb and resource: reading a system description and building a threat-modelling starting point, with the specific six-lens STRIDE matrix and prioritized outputs. It clearly distinguishes this tool from security-adjacent siblings such as security_requirements_checklist and review_security_posture by focusing on threat-model draft generation.

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 description gives clear context for use: it fits situations where a system description exists and a threat-model starting point is needed, and it notes that different exposure contexts (public portal vs isolated IoT) change the output. It does not explicitly name alternatives or state when not to use it, 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.

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