「policy」の検索結果

Use when you need to apply Java exception handling best practices — including using specific exception types, managing resources with try-with-resources, securing exception messages, preserving error context via exception chaining, validating inputs early with fail-fast principles, handling thread interruption correctly, documenting exceptions with @throws, enforcing logging policy, translating exceptions at API boundaries, managing retries and idempotency, enforcing timeouts, attaching suppressed exceptions, and propagating failures in async/reactive code. This should trigger for requests such as Exception handling; Use try-with-resources in Java code; Create exception chaining in Java code; Apply fail-fast validation in Java code; Review Java exception taxonomy and propagation. Part of Plinth Toolkit

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Builds a product strategy and stress-tests your moat, then writes a one-page strategy doc (diagnosis, where to play, how to win, guiding policy, coherent actions, moat verdicts). Use for 'we need a product strategy', 'is our moat real', 'do we have a competitive advantage', 'where should we play', 'defensibility', 'should we expand into X', 'our roadmap has no strategy', or 'write a product vision'. Draws on 909 insights from 236 Lenny's Podcast guests incl. Roger Martin, Richard Rumelt and Hamilton Helmer.

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Sets up how you and your team build and work with AI agents, and produces an Agent Workflow Charter (agent lanes, plan-mode loop, autonomy ladder with promotion criteria, rules file, review policy, security rules, rollout plan). Use when you ask 'how should we work with Claude Code / Codex / Cursor', 'how many agents should I run', 'should the agent be autonomous', 'plan mode', 'CLAUDE.md', 'AI-native team', 'roll out AI to my team', or 'my agent keeps screwing up'. Draws on 110 Lenny's Podcast guests incl. Claire Vo, Boris Cherny and Aishwarya Naresh Reganti.

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Automate payer review of prior authorization (PA) requests. This skill should be used when users say "Review this PA request", "Process prior authorization for [procedure]", "Assess medical necessity", "Generate PA decision", or when processing clinical documentation for coverage policy validation and authorization decisions.

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Find leaked secrets in source code, Git history, build artifacts, and infrastructure — and audit the secrets-management posture preventing future leaks. Use when the user mentions 'secrets audit,' 'secret scanning,' 'leaked credentials,' 'API key in code,' 'gitleaks,' 'trufflehog,' 'git history scan,' 'secrets management,' 'vault audit,' 'rotation policy,' 'AWS Secrets Manager,' 'HashiCorp Vault,' 'Doppler,' '1Password Secrets Automation,' 'sealed-secrets,' 'External Secrets Operator,' or needs to find or prevent credential exposure.

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Bring an existing codebase into Dryforge, once. Reads the code, asks what code cannot show — business rules, security policy, what is intentional — and writes the project docs at the entry points agents already read. Use when the user invokes the `migration` skill on an existing project. Requires git.

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HTML, CSS, and JavaScript craft guidelines from bendc/frontend-guidelines — semantics, a11y basics, selector discipline, motion-friendly CSS, and readable JS. Use for markup review, static HTML/CSS, email HTML, or general front-end hygiene; pair with repo frontend rules and TypeScript lint policy.

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AiZynthFinder retrosynthetic route planning (CASP) from AstraZeneca Molecular AI. Monte Carlo tree search guided by a template-based neural expansion policy recursively disconnects a target SMILES until precursors are found in a purchasable stock. Covers config.yml (v4 format), aizynthcli batch screening, the AiZynthFinder/AiZynthExpander Python API, one-step disconnections, custom stocks via smiles2stock, scorers, Retro*/breadth-first/DFPN search alternatives, and reading output.json.gz / trees.json. Use for synthesis route planning, synthesizability screening, and building-block/precursor search. For reaction barriers use neb-irc-activation-energy; for 2D reaction scheme drawing use rdkit-chemdraw-cdxml.

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NEJM figure preparation: resolution (300-1200 DPI), editable vector formats (AI/EPS/SVG), in-house medical illustration policy, and strict image integrity requirements.

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eLife figure preparation: file formats (TIFF/EPS/PDF), striking image requirements (1800x900 px), figure supplement naming, and image screening policy treating selective enhancement as misconduct.

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The Lancet figure preparation: resolution (300+ DPI at 120%), preferred editable formats (PowerPoint/Word/SVG), column widths (75/154 mm), Times New Roman, in-house redraw policy.

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SST v4 (Ion) expert for managing AWS resources as code with the Pulumi-backed framework. Use when writing or editing sst.config.ts, building infra/ modules (sst.aws.Function/Bucket/Dynamo/Cron/Service/Router, sst.Secret, sst.Linkable, raw aws.* Pulumi resources), wiring resource links, scoping IAM, or running sst deploy/dev/diff/remove. Essential when the user mentions SST, sst.config.ts, $config, $transform, $interpolate, sst.aws.*, sst.Secret, Pulumi/Ion, "sst deploy", a failed SST deploy (ConflictException on a resource-type change, "Identifier '__filename' has already been declared", MalformedPolicyDocument on an Output<T>), or wants to scaffold/troubleshoot AWS infrastructure with SST. Also use when a request to "deploy my AWS stack" or "add a Lambda/bucket/table" is made in a repo that already contains an sst.config.ts (using $config) or an sst dependency. Do NOT use when the task is primarily AWS CDK, Terraform, raw CloudFormation, or SAM with no SST present — those have their own tooling.

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Build or modernize an employee handbook for a small business with no HR department -- interviews the owner for actual practices, drafts every core policy in plain English, flags the state-specific requirements that need local verification, and outputs a document employees might actually read.

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Cowork-style sweep of a folder of receipts, statements, and expense exports -- categorizes every transaction, matches receipts to statement lines, flags policy violations and anomalies, and outputs a clean expense report plus a findings memo.

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Use when choosing where to submit a manuscript. Matches the abstract against curated journal profiles and returns ranked picks with scope fit, AI-disclosure policy, an acceptance-readiness pre-flight and a reject-fallback cascade. Impact and APC figures may be stale.

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Use when a paper needs publication-ready figures or a visual abstract. Makes ROC, forest, calibration, Kaplan-Meier and Bland-Altman plots, CONSORT/STARD/PRISMA flow diagrams, confusion matrices, pipeline diagrams and journal visual abstracts, checking the journal's AI-image policy first.

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Guide ROS/Gazebo Velodyne mobile-robot navigation with the DRL-robot-navigation TD3 implementation, including simulator setup, environment contracts, bounded training, checkpoints, and policy evaluation.

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Guide agents through AgiBot X1 humanoid reinforcement-learning training, checkpoint playback, policy export, and MuJoCo sim2sim workflows with verified configuration contracts and explicit Isaac Gym limits.

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Routes ACT++, ACT, Diffusion Policy, VINN, and MuJoCo simulation workflows for bimanual ALOHA episode data and imitation-learning tasks.

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Implements email and internet monitoring compliance in the workplace per Barbulescu v Romania (ECHR Grand Chamber), EDPB guidance, and national labour law. Covers acceptable use policies, legitimate expectation of privacy, proportionality testing, and content vs metadata monitoring. Keywords: email monitoring, Barbulescu, workplace privacy, internet monitoring, acceptable use policy, ECHR, proportionality.

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Designs and implements data retention schedules compliant with GDPR Article 5(1)(e) storage limitation principle. Maps data categories to retention periods with legal basis justification, regulatory minimum holding periods, and automated review triggers for schedule maintenance. Activate for retention policy, storage limitation, data lifecycle, retention period queries.

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Implements HIPAA workforce training requirements under 45 CFR §164.530(b) (Privacy Rule) and 45 CFR §164.308(a)(5) (Security Rule). Covers initial onboarding training, periodic refresher cadence, role-based content differentiation, documentation of training completion, and sanction policy integration. Keywords: HIPAA training, workforce training, security awareness, privacy training, §164.530(b), §164.308(a)(5).

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Implements BYOD privacy compliance frameworks for personal device use in the workplace. Covers personal vs corporate data separation, MDM capabilities and limitations, employee consent requirements, data wiping boundaries, and monitoring restrictions on personal devices. Keywords: BYOD, mobile device management, MDM, personal device, data separation, containerisation, remote wipe, employee privacy.

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Configures cloud storage retention policies across AWS S3, Azure Blob Storage, and Google Cloud Storage. Covers lifecycle rules, object lock, legal hold, immutability policies, cross-region replication retention alignment, and compliance mode configuration. Activate for cloud retention, S3 lifecycle, Azure retention, GCP retention policy queries.

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。