Perform language and framework specific security best-practice reviews and suggest improvements. Trigger only when the user explicitly requests security best practices guidance, a security review/report, or secure-by-default coding help. Trigger only for supported languages (python, javascript/typescript, go). Do not trigger for general code review, debugging, or non-security tasks.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
This skill provides a description of how to identify the language and frameworks used by the current context, and then to load information from this skill's references directory about the security best practices for this language and or frameworks.
This information, if present, can be used to write new secure by default code, or to passively detect major issues within existing code, or (if requested by the user) provide a vulnerability report and suggest fixes.
The initial step for this skill is to identify ALL languages and ALL frameworks which you are being asked to use or already exist in the scope of the project you are working in. Focus on the primary core frameworks. Often you will want to identify both frontend and backend languages and frameworks.
Then check this skill's references directory to see if there are any relevant documentation for the language and or frameworks. Make sure you read ALL reference files which relate to the specific framework or language. The format of the filenames is <language>-<framework>-<stack>-security.md. You should also check if there is a <language>-general-<stack>-security.md which is agnostic to the framework you may be using.
If working on a web application which includes a frontend and a backend, make sure you have checked for reference documents for BOTH the frontend and backend!
If you are asked to make a web app which will include both a frontend and backend, but the frontend framework is not specified, also check out javascript-general-web-frontend-security.md. It is important that you understand how to secure both the frontend and backend.
If no relevant information is available in the skill's references directory, think a little bit about what you know about the language, the framework, and all well known security best practices for it. If you are unsure you can try to search online for documentation on security best practices.
From there it can operate in a few ways.
The primary mode is to just use the information to write secure by default code from this point forward. This is useful for starting a new project or when writing new code.
The secondary mode is to passively detect vulnerabilities while working in the project and writing code for the user. Critical or very important vulnerabilities or major issues going against security guidance can be flagged and the user can be told about them. This passive mode should focus on the largest impact vulnerabilities and secure defaults.
The user can ask for a security report or to improve the security of the codebase. In this case a full report should be produced describe anyways the project fails to follow security best practices guidance. The report should be prioritized and have clear sections of severity and urgency. Then offer to start working on fixes for these issues. See #fixes below.
references/, load only the relevant files and follow their instructions.While these references contain the security best practices for languages and frameworks, customers may have cases where they need to bypass or override these practices. Pay attention to specific rules and instructions in the project's documentation and prompt files which may require you to override certain best practices. When overriding a best practice, you MAY report it to the user, but do not fight with them. If a security best practice needs to be bypassed / ignored for some project specific reason, you can also suggest to add documentation about this to the project so it is clear why the best practice is not being followed and to follow that bypass in the future.
When producing a report, you should write the report as a markdown file in security_best_practices_report.md or some other location if provided by the user. You can ask the user where they would like the report to be written to.
The report should have a short executive summary at the top.
The report should be clearly delineated into multiple sections based on severity of the vulnerability. The report should focus on the most critical findings as these have the highest impact for the user. All findings should be noted with an numeric ID to make them easier to reference.
For critical findings include a one sentence impact statement.
Once the report is written, also report it to the user directly, although you may be less verbose. You can offer to explain any of the findings or the reasons behind the security best practices guidance if the user wants more info on any findings.
Important: When referencing code in the report, make sure to find and include line numbers for the code you are referencing.
After you write the report file, summarize the findings to the user.
Also tell the user where the final report was written to
If you produced a report, let the user read the report and ask to begin performing fixes.
If you passively found a critical finding, notify the user and ask if they would like you to fix this finding.
When producing fixes, focus on fixing a single finding at a time. The fixes should have concise clear comments explaining that the new code is based on the specific security best practice, and perhaps a very short reason why it would be dangerous to not do it in this way.
Always consider if the changes you want to make will impact the functionality of the user's code. Consider if the changes may cause regressions with how the project works currently. It is often the case that insecure code is relied on for other reasons (and this is why insecure code lives on for so long). Avoid breaking the user's project as this may make them not want to apply security fixes in the future. It is better to write a well thought out, well informed by the rest of the project, fix, then a quick slapdash change.
Always follow any normal change or commit flow the user has configured. If making git commits, provide clear commit messages explaining this is to align with security best practices. Try to avoid bunching a number of unrelated findings into a single commit.
Always follow any normal testing flows the user has configured (if any) to confirm that your changes are not introducing regressions. Consider the second order impacts the changes may have and inform the user before making them if there are any.
Below is a few bits of secure coding advice that applies to almost any language or framework.
When assigning an ID for some resource, which will then be used by exposed to the internet, avoid using small auto-incrementing IDs. Use longer, random UUID4 or random hex string instead. This will prevent users from learning the quantity of a resource and being able to guess resource IDs.
While TLS is important for production deployments, most development work will be with TLS disabled or provided by some out-of-scope TLS proxy. Due to this, be very careful about not reporting lack of TLS as a security issue. Also be very careful around use of "secure" cookies. They should only be set if the application will actually be over TLS. If they are set on non-TLS applications (such as when deployed for local dev or testing), it will break the application. You can provide a env or other flag to override setting secure as a way to keep it off until on a TLS production deployment. Additionally avoid recommending HSTS. It is dangerous to use without full understanding of the lasting impacts (can cause major outages and user lockout) and it is not generally recommended for the scope of projects being reviewed by codex.
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概要と使いどころ
Creates an Agent Authority Charter for enterprise or regulated AI agents before deployment. Use this Skill when a user needs to define what an AI agent is allowed to do, who delegated authority to it, what actions are permitted or prohibited, when human approval is required, what evidence must be preserved, and how the agent can be suspended, revoked, or escalated.
日本語の概要は準備中です。原文の説明を表示しています。
EU AI Act Knowledge Engine — authoritative regulatory Q&A grounded in 70 official EU source documents (including the 2026 Commission draft guidelines on Art. 6 high-risk classification — general principles, Annex I, Annex III). Answers any question about the AI Act with article-level citations from the full regulation text, Commission guidelines, EDPB/EDPS opinions, codes of practice, harmonised standards, FRIA guides, incident templates, and sector-specific guidance. This skill should be used when the user asks about the "EU AI Act", "AI Act regulation", "Regulation 2024/1689", "KI-Verordnung", asks to "explain an AI Act article", "what does Article X say", "AI Act requirements", "AI Act penalties", "AI Act timeline", "GPAI obligations", "high-risk AI", "prohibited AI practices", "AI Act and GDPR", "fundamental rights impact assessment", "AI Act standards", "AI Act national implementation", "AI literacy", "serious incident reporting", "Digital Omnibus", "AI regulatory sandbox", or any question about EU artificial intelligence regulation. Also triggers on German terms: "KI-Gesetz", "KI-Verordnung", "Hochrisiko-KI", "KI-Kompetenz", "Grundrechte-Folgenabschaetzung", "GPAI-Verhaltenskodex". For assessment workflows that produce a classification decision rather than a knowledge answer, offer to run a structured risk-tier classification in-session.
日本語の概要は準備中です。原文の説明を表示しています。
This skill builds a structured audit trail of an AI-assisted task: what the tool was asked to do, what materials it was given, what it produced, how the output was verified, and what was ultimately relied upon. It documents the workflow for supervision and later review without ruling on privilege or disclosure, so the record stays accurate rather than self-serving.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill when the user wants an AI governance, legal-risk, privacy, compliance, procurement, or vendor-risk review of an internal AI use case, an AI product feature, an LLM workflow, or a third-party AI vendor. The skill asks intake and clarifying questions first when facts or evidence are missing, identifies required documentation and missing evidence, maps the use case to AI governance frameworks and applicable legal domains, and produces a preliminary or final governance review with scorecards, findings, owners, remediation actions, and follow-up questions.
日本語の概要は準備中です。原文の説明を表示しています。
Turn an interpretive-ambiguity audit of a legal text — contract, statute, regulation, or judicial opinion — into a polished deliverable. Produces a multi-page website (default), a single-page interactive site, a Microsoft Word document, a PowerPoint deck, or a LaTeX/PDF. Use whenever a user has a stress-test result, ambiguity audit, or "where will this be litigated" scenarios and wants to publish, present, or share them. Triggers on "publish the audit," "make a report from this," "turn this into a website / deck / brief / Word doc," "make a Netlify site," "build slides of these ambiguities," "render the scenarios," "package this stress test," "produce a LaTeX version," and similar. Pairs with the ambiguity-stress-test skill (the underlying analysis) but works on any structured or semi-structured ambiguity analysis. Visual design is opinionated but the user can override colors, fonts, and brand label. Most formats need Python and a writable filesystem; single-file HTML works where the host has neither.
日本語の概要は準備中です。原文の説明を表示しています。
Adversarially stress-tests a legal text — a contract, statute, regulation, or judicial opinion — for interpretive ambiguity: it finds the seams where the people governed by it will later disagree about what it means and turns each into a concrete dispute scenario with both sides' arguments, the likely outcome, and a fix. Use it whenever someone wants to pressure-test, red-team, audit, or find weak spots, loopholes, gaps, ambiguities, or drafting problems in a legal document; whenever a drafter wants to tighten a contract, statute, regulation, or opinion before it issues; whenever a litigator wants to mine an opinion or contract for arguments; or whenever someone hands over a legal text and asks where it will be fought over or for issue-spotting. Trigger it for contract review, statutory-ambiguity analysis, judicial-opinion scope analysis, and drafting QA — even if the user never says "stress-test" or "ambiguity."
日本語の概要は準備中です。原文の説明を表示しています。