“long context”的搜索结果

Maintain SESSION-STATE.md, the durable within-session memory that survives context compaction. Use when a constraint, settled decision, existing-infrastructure (survey) finding, or open thread must persist across a long session so it is not re-derived or re-litigated. Triggers on /state, "remember this for the session", "record this constraint/decision", or after surveying what already exists. For cross-session/personal memory use .claude/memory/ on Claude or native memories on Codex; for repo-derivable facts, do not record at all.

中文简介正在准备中。当前显示原文说明。

Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them.

中文简介正在准备中。当前显示原文说明。

Load before the first bd command of any kind (reads included) in every session, even when bd prime context is already present. Applies reusable Beads writing and update practices when reading, creating, updating, commenting on, closing, superseding, or handing off Beads issues, alongside beads, beads-solo, and plan-to-beads workflows.

中文简介正在准备中。当前显示原文说明。

Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.

中文简介正在准备中。当前显示原文说明。

Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them.

中文简介正在准备中。当前显示原文说明。

Modelo de espaço de estados com complexidade O(n) versus O(n²) dos Transformers. Inferência 5× mais rápida, sequências de milhão de tokens, sem cache KV. SSM seletivo com design aware de hardware. Mamba-1 (d_state=16) e Mamba-2 (d_state=128, multi-head). Modelos 130M-2.8B no HuggingFace.

中文简介正在准备中。当前显示原文说明。

Memória é a base de agentes inteligentes. Sem ela, cada interação começa do zero. Esta skill cobre a arquitetura de memória de agentes: curto prazo (janela de contexto), longo prazo (vector stores), e as arquiteturas cognitivas que as organizam. Insight-chave: Memória não é apenas armazenamento - é recuperação. Um milhão de fatos armazenados não significam nada se você não conseguir encontrar o certo. Estratégias de chunking, embedding e recuperação determinam se seu agente se lembra ou esquece. O campo é fragm

中文简介正在准备中。当前显示原文说明。

Audit and optimize a skill system with evidence. Use for skill architecture, token or context waste, role and prompt boundaries, routing hits or misfires, plugin packaging, registry/docs/source drift, duplicate workflows, or deciding whether a reusable change belongs in a skill. Runs deterministic checks first and applies only authorized, minimal fixes.

中文简介正在准备中。当前显示原文说明。

Use when a long session should continue in a fresh agent — context is nearly full, compaction would lose detail, or the work is moving to another tool or teammate. Compacts the conversation into a handoff document in the OS temp directory, pointing at existing specs, plans, and diffs instead of repeating them.

中文简介正在准备中。当前显示原文说明。

Use when long-lived agents, project memories, system prompts, or playbooks are repeatedly summarized, rewritten, or optimized and risk losing domain detail, provenance, or execution learnings.

中文简介正在准备中。当前显示原文说明。

Use when designing long-horizon agents that need subagents, isolated context windows, filesystem-backed work, persistence, human approval, MCP tools, or production tracing.

中文简介正在准备中。当前显示原文说明。

Create, verify, transfer, and resume compact project handoff packets for long-running Codex work. Use after a second observed automatic context compaction, immediately after a third compaction, when attention or constraints degrade, a major phase ends, the user asks to move work into a fresh task, work must pause, or an existing handoff needs to be imported. Do not interrupt after the first normal compaction. Always ask before creating a new task, transfer the global roadmap only after explicit consent, preserve the old task title when available, then require the fresh task to ask what work matters most. Preserve objectives, constraints, decisions, evidence, approval boundaries, workspace state, validation, and risks without treating an old summary as current truth.

中文简介正在准备中。当前显示原文说明。

Track Two / internal innovation system for running small, fast experiments outside the core business. Runs in three modes — Diagnostic for designing the full Protoloop from scratch (intake channels, loop structure, team, exit paths), Review for running the monthly heartbeat meeting (loop-by-loop decisions, forward-loading, portfolio health), and Alert Triggers for defining tripwires that protect, feed, and maintain momentum in the system. Updates company-context.md after every run. Triggers on questions about innovation pipelines, intrapreneurship, Track Two strategy, experimentation systems, handling ideas that don't fit the core business, or building systematic exploration alongside exploitation. Based on 20 years of practice by Eterdis (eterdis.com).

中文简介正在准备中。当前显示原文说明。

Use for role-scoped FE/BE/DevOps/Admin/QA project docs under .codex/project-docs to preserve micro-context across long projects.

中文简介正在准备中。当前显示原文说明。

Turns one long support ticket thread (helpdesk history, email chain, chat transcript, call notes) into a one-page DRAFT escalation summary: the customer's ask in their own words, account context as stated, a dated history, what was tried and the stated result of each attempt, the current state, and what is needed from whom by when, every line referenced to a message and every missing fact marked UNKNOWN. Use when the user asks to "escalate this ticket", "summarise this thread for tier two", "write the hand-over for this case", "what has been tried so far", "brief engineering on this customer issue" or "prepare the escalation note". Do not use for a batch of tickets, use ticket-triage-pack instead; for the review after an outage, use incident-postmortem-drafter. Drafts for human review; never approves, authorises or signs off.

中文简介正在准备中。当前显示原文说明。

Use the WooCommerce REST API v4 (namespace wc/v4, since WC 10.2) alongside or in place of v3 — verified route catalog (Customers, Orders, Refunds, Products, ShippingZones with DELETE, ShippingZoneMethod, Fulfillments, segmented Settings under /wc/v4/settings/<group>), the hook prefix pattern woocommerce_rest_api_v4_<route>_*, shared error codes, and the RestApiCache trait (WC 10.5+) for endpoint response caching. The v4 AbstractController lives under the Internal namespace and is NOT a public extension surface; plugin-defined REST routes use WP_REST_Controller directly. Use when calling WC REST endpoints, when picking v3 vs v4, or when reviewing /wc/v3/ URLs that now have v4 equivalents. Triggers on wc/v4, /wc/v4/, woocommerce_rest_api_v4_*, RestApiCache, customer-owned Woo endpoints, REST API v4 in WooCommerce context.

中文简介正在准备中。当前显示原文说明。

Guide for using MSBuild Server to improve CLI build performance. Only activate in MSBuild/.NET build context. Activate when developers report slow incremental builds from the command line, or when CLI builds are noticeably slower than IDE builds. Covers MSBUILDUSESERVER=1 environment variable for persistent server-based caching. Do not activate for IDE-based builds (Visual Studio already uses a long-lived process).

中文简介正在准备中。当前显示原文说明。

Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector s...

中文简介正在准备中。当前显示原文说明。

Configure Netlify projects via netlify.toml and the _headers/_redirects files — covering build settings and deploy contexts alongside environment variables/scopes and the Secrets Controller plus redirect/rewrite/proxy and custom-header rules. Use when setting a build command or publish directory, adding redirect or rewrite or proxy rules, configuring custom headers or basic auth, setting or scoping environment variables and secrets, wiring up a monorepo or SPA fallback, or skipping unnecessary builds. Reach for this whenever you touch netlify.toml or ask "why is my env var undefined in a function" or "how do I redirect this path".

中文简介正在准备中。当前显示原文说明。

Write, configure, and deploy Netlify serverless functions in TypeScript, JavaScript, or Go. Use this when adding an API endpoint or backend route, adding a contact form handler, wiring auth or Identity signup/login hooks, building streaming or AI-proxy responses, scheduling cron jobs, running long background jobs (batch processing/scraping), reacting to deploy or form events, setting up rate limiting or region/memory config, or reading environment variables and secrets inside a function. Covers file locations, the Request/Context/Response handler shape, path routing, config options, and local testing with netlify dev.

中文简介正在准备中。当前显示原文说明。

Motion / animation context for the `use_figma` MCP tool — animating Figma nodes via manual keyframes, animation styles, easing, and timeline duration. Load alongside figma-use whenever a task involves adding, editing, or inspecting animation on a node.

中文简介正在准备中。当前显示原文说明。

Write a compact, decision-ready handoff so the next session (or the user) can continue without reconstructing the current one. Use when the session is ending, context is running low, the user asks for a handoff / 'pass the baton' / 'hand off', or a long-running operation needs a durable state checkpoint.

中文简介正在准备中。当前显示原文说明。

Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragm

中文简介正在准备中。当前显示原文说明。

Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.

中文简介正在准备中。当前显示原文说明。