Results for “ai-native”

Design agent tools and CLI surfaces—schemas, naming, errors, idempotency, and discoverability for LLM callers. Use when defining tools for agents, SDKs, or AI-native CLIs.

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Establish project thesis before first code. Infer product type from domain/folder/README. Identify users, business model, pSEO strategy, AI-native dev approach. Maintain PROJECT_BRIEF.md as source of truth.

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Manage Volcengine's AI-native BaaS platform (Supabase edition / AIDAP / 火山引擎 AI 原生 BaaS 平台 Supabase 版) — a Volcengine-operated distribution that differs from official Supabase. Use when the user asks to create, inspect, or manage Volcengine Supabase or AIDAP resources — workspaces, branches, computes, SQL queries, schema changes, Auth, Realtime, Edge Functions, Storage buckets, frontend static-site hosting (Pages), API keys, connection info, or TypeScript type generation — or when a Volcengine deployment selects AIDAP as its database provider. Also trigger on Chinese prompts mentioning "火山引擎 Supabase" or "火山 Supabase". Operations run through the byted-supabase-cli command-line tool (installed via `npm i -g @byted-supabase/cli`; this is NOT the official `supabase` CLI). Do NOT use it for general database discussions, non-Supabase services (RDS MySQL, Redis), or pure client-side coding unrelated to Supabase backend management.

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AI-native accounting for UK micro-businesses. Use when the user wants to track transactions, manage VAT, check deadlines, or do any bookkeeping for a UK limited company.

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Design spec with 98 rules for building CLI tools that AI agents can safely use. Covers structured JSON output, error handling, input contracts, safety guardrails, exit codes, and agent self-description.

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Convert human-written CLAUDE.md into AI-native structured-label format. Battle-tested across 4 models. Same rules, fewer tokens, higher compliance.

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PRD 架构师 / 需求文档起草：当用户要把一个产品想法、需求草稿、脑暴结果或功能说明整理成 PRD 时使用。 可用中文唤起：“帮我写 PRD”“帮我选 PRD 模板”“把这个需求整理成 PRD”“判断该用轻量 PRD 还是标准 PRD” “补一张可编辑 Draw.io 核心流程图”“PRD 里加架构图”。 会在 PRD-lite、PRD-standard、PRD-ai-native 中选择一个模板资产按需加载，并在需要时加载 mockup handoff、 Draw.io 图示或开发 handoff 附录；页面型 PRD 默认联动生成项目 UI 对齐的 HTML、关键截图和正文证据。 不用于直接编码、单纯画 UI，或评审一份已经写好的 PRD。

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The AI native file format. EXIF for AI — stamps every file with trust scores, source provenance, and compliance metadata. Embeds into 20+ formats (DOCX, PDF, images, code). EU AI Act, SOX, HIPAA auditing.

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Design spec with 98 rules for building CLI tools that AI agents can safely use. Covers structured JSON output, error handling, input contracts, safety guardrails, exit codes, and agent self-description.

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Convert human-written CLAUDE.md into AI-native structured-label format. Battle-tested across 4 models. Same rules, fewer tokens, higher compliance.

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Maintain vision, user journeys, evolving requirements and roadmap outcomes when intent or acceptance changes.

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Map requirement acceptance to proportionate executable checks and real user journeys before implementation and completion.

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Challenge vision alignment, value, cost, risk and operating ownership at material scope or release decisions.

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AI-native accounting for UK micro-businesses.

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Read-only SRE checkup of any GCP project: deterministic probes of the edge, Cloud Run services, 7-day error logs, Cloud Scheduler, alert policies and uptime checks, Secret Manager and IAM, the data stores and the machine's own scheduled jobs, audited into one fixed status table (LIVE / WARNING / RED / INCONCLUSIVE) with evidence, findings by severity, what could not be checked, and a single OVERALL line delivered as one notification. Parametrised by a per-project manifest, so the same routine runs on every project. Use when the operator says "cloud checkup", "SRE check", "is everything live", "what's healthy / warning / red", "any errors this week", "audit the infra", "weekly checkup", "set up the weekly checkup", before a deploy or demo, or after an incident. Cloud Run first; App Engine and GKE differ only in the serving probes.

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Check proposed stack, data flows, cloud choices, and delivery controls against declared enterprise policies, compliance frameworks, and security controls. Trigger at R2/R3 risk classification, before locking architecture decisions, or when the operating profile names a governance pointer.

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Architecture decisions, trade-off analysis, and ADR authoring. Trigger when a significant technical decision needs to be made, documented, and owned — not when an implementation detail needs a choice.

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Use when configuring or optimising GitHub repositories for cost-effective, consistent operations — CI triggers, Actions billing, issue tracking, labelling, branch protection, or release workflow.

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Govern the SemVer release process — versioning discipline, tag-based GitHub releases, changelog hygiene, and the ADR that confirms the release strategy is agreed. Trigger when setting up a release process, before a first public release, or when release practice has become inconsistent. Owned by delivery-orchestrator.

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Govern discovery, eligibility, and submission of a plugin or skill to official directories, registries, marketplaces, and curated GitHub lists. Use when preparing or sending plugin listings, marketplace forms, directory PRs, or repository recommendations; require current policy evidence and a final human confirmation before every external submission.

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Pursue an agreed goal to a working outcome without waiting: decompose it, re-prioritise as evidence arrives, branch, gate, get an independent review (a different model or a fresh reviewer subagent — the writer never approves), merge, prune, and bank the operator's decisions in STATUS.md instead of blocking on them. Trigger on "get it done", "don't wait for me", "proceed autonomously", or when an epic or roadmap objective is handed over. Not a close-out: this work set is expected to grow.

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Validate agent output against declared domain rules and ground truth before trusting it downstream. Trigger after any agent produces output that will be used in a decision, stored persistently, or passed to another agent.

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Decompose an epic into atomic parallelizable tasks, route each to the right skill, and keep the four delivery records straight — issues, STATUS, ROADMAP, CHANGELOG. Use as a meta-router when several skills could apply, and as the baseline for how delivery state is recorded. Trigger at the start of any multi-track epic, when the skill count exceeds ~12, or when the records have drifted from reality.

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LLM and cloud cost awareness — model tiering, token budgets, right-sizing, and when a cheaper model suffices. Trigger before finalising any architecture that calls LLMs, before scaling a workload, or when a cost estimate is needed.

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