Skills
98,639 packaged capabilities and playbooks for agents. Install any of them with one command.
All
Use when the user asks to “build my brand-safety exclusion lists”, “set placement / topic / content exclusions before launch”, “add network and audience exclusions”, or “prep the A1 brand-safety evidence for the auditor”; produces a placement/network exclusion list, a content-suitability & sensitive-topic block list, an audience/negative-audience exclusion set, and a packaged A1 brand/placement-safety evidence file for the gate. Not for building the audiences you target — use audience-segment-builder; not for computing the RQS or issuing the A1 verdict — use ad-account-auditor. 品牌安全/排除位置/否定受众列表
Use when the user asks to "map our positioning", "name our competitive alternatives", or "pick a beachhead segment for the launch"; produces a Dunford-style positioning canvas — named competitive alternatives (including spreadsheet and status quo), unique attributes (verifiable, or routed to the claims ledger), value themes (attribute→benefit→value chains), a target beachhead segment scored on serviceability / pain intensity / reachability, and a one-sentence onlyness statement — the sole upstream of the message house and the entity-signal source for the canonical entity profile. Not for the message house or per-channel launch copy — use message-house-builder; not for audience/persona profiling itself — use audience-mapper; not for SEO keyword positioning — use keyword-research. 定位画布/竞争替代品/独特价值/滩头细分
Use this skill when designing, generating an MVP blueprint for, auditing, troubleshooting, refactoring, or explaining an agentic harness for any domain. Covers provider-neutral agent architecture for OpenAI, Anthropic, and OpenAI-compatible APIs: agent loops, tool design, record provenance, interactive presentation, user-memory lifecycles, environment-adaptive tools, speculative tool execution, late-bound capabilities, permissions, system prompts, planning, goals, always-on agents and durable runtime, adaptive agent teams, context compaction, memory, skills, MCP/external connectors, public-board communications, realtime voice agents, hardware agents and board deployment, self-refining recursive harnesses, programmable context, continual refinement, observability, evals, prompt caching, agent-legible environments, feedback loops, and safety.
Generate AI music and songs with ElevenLabs, Diffrythm, Tencent Song Generation via inference.sh CLI. Models: ElevenLabs Music (up to 10 min, commercial license), Diffrythm (fast song generation), Tencent Song Generation (full songs with vocals). Capabilities: text-to-music, song generation, instrumental, lyrics to song, soundtrack creation. Use for: background music, social media content, game soundtracks, podcasts, royalty-free music. Triggers: music generation, ai music, generate song, ai composer, text to music, song generator, create music with ai, suno alternative, udio alternative, ai song, ai soundtrack, generate soundtrack, ai jingle, music ai, beat generator, elevenlabs music, eleven labs music
Use when the user asks to "pick which social channels to run", "should we be on X platform or 小红书", or "plan our organic social channel portfolio"; produces an audience/objective-first portfolio with capability/access matrix, cadence-budget reality check, declared ECHO operating profile, boundary routing, and proposed-state registry events. Not for recording canonical channel facts — use channel-registry. 社媒渠道选择/渠道组合规划/平台能力矩阵/自然社媒
Use when the user asks to “launch on Product Hunt / Hacker News”, “prepare community or directory launch submissions”, or “plan the launch submission waves”; produces per-platform submission packages — a Product Hunt tagline / gallery / first-comment skeleton, a factual Show HN title and text, per-subreddit posts with a self-promotion rules table, tiered directory waves, and a regional channel matrix including Chinese communities — plus a platform red-line check (never solicit votes or organize voting rings) and T-0 submission-status lines for the launch registry. Not for paid amplification — use content-amplifier; not for creator channels — use campaign-planner; not for launch telemetry readouts — use launch-monitor; not for ongoing community presence or pre-launch karma-building outside the launch window — use participation-warmup-planner. 社区发布/PH提交包/Show HN/目录波次/平台红线/中文渠道
Use when the user asks to “figure out where our direct traffic really comes from”, “measure dark social”, “add a how-did-you-hear-about-us field”, or “show social drives signups without click data”; produces a share-link/UTM hygiene spec for owned share surfaces, a self-reported attribution field design that replaces an existing form field (free-text first, coded later), a GA4 direct-traffic decomposition read (deep-URL directs, mobile-app skew, private-push correlation) with every derived number hard-labeled Estimated/proxy, and a branded-search-lift proxy from GSC plus Wikipedia pageviews — the declared dark-social method behind ECHO O2. Not for paid-channel attribution reconciliation (platform-claimed vs analytics conversions) — use attribution-reconciler. 暗社交归因/直接流量分解/自报来源字段/分享链路UTM
Guides evaluation of RAG pipeline retrieval and generation quality. Use when evaluating a retrieval-augmented generation system, measuring retrieval quality, assessing generation faithfulness or relevance, generating synthetic QA pairs for retrieval testing, or optimizing chunking strategies.
JavaScript/TypeScript SDK for inference.sh - run AI apps, build agents, integrate with all models. Package: @inferencesh/sdk (npm install). Full TypeScript support, streaming, file uploads. Build agents with template or ad-hoc patterns, tool builder API, skills, human approval. Use for: JavaScript integration, TypeScript, Node.js, React, Next.js, frontend apps. Triggers: javascript sdk, typescript sdk, npm install, node.js api, js client, react ai, next.js ai, frontend sdk, @inferencesh/sdk, typescript agent, browser sdk, js integration
Choosing what form your data needs for MapLibre GL JS — GeoJSON read straight from a file versus vector or raster tiles, the feature-count and file-size thresholds where each stops working, and how a basemap and your own data combine as separate sources. Use when deciding which source type a dataset needs, not when hosting or configuring one
Apply when implementing retry logic, rate limit handling, or resilience patterns in VTEX API integrations. Covers VTEX rate limit headers (X-RateLimit-Remaining, X-RateLimit-Reset, Retry-After), 429 status handling, exponential backoff with jitter, circuit breaker patterns, and request queuing. Use for any VTEX marketplace integration that must gracefully handle API throttling and maintain high availability.
Python SDK for inference.sh - run AI apps, build agents, and integrate with all models. Package: inferencesh (pip install inferencesh). Supports sync/async, streaming, file uploads. Build agents with template or ad-hoc patterns, tool builder API, skills, and human approval. Use for: Python integration, AI apps, agent development, RAG pipelines, automation. Triggers: python sdk, inferencesh, pip install, python api, python client, async inference, python agent, tool builder python, programmatic ai, python integration, sdk python
Rebuilds an app's design system for a clone: colour roles, type scale, spacing, radius, shadows and every component with its states, as design tokens plus component specs, with original assets instead of the target's logos, icons, illustrations or licensed fonts. Includes a WCAG contrast checker. Use when the user says "match the design", "rebuild the design system", "get the colours and fonts", "make it look like X", "design tokens for my clone", or after /replica-architect.
Use when the user asks to “calculate influencer ROI”, “prove campaign value”, or “what was our ROAS”; produces direct ROI/ROAS, earned media value, attribution-modeled revenue, LTV-based ROI, and a stakeholder-ready summary. Not for building the full slide/written report — use report-generator. 达人营销ROI计算/投资回报测算
Use when the user asks to “design an employee advocacy program”, “set up founder-led sharing”, or “build a share kit for the team”; produces an advocacy program blueprint in two modes — participation-driven opt-in (default) or top-down assigned with its coercion and authenticity risks flagged — with a voluntary opt-in roster spec submitted as channel-registry proposal events, share kits with mandatory per-person variation, staggered human posting windows plus anti-pod guardrails (no coordinated identical reshares, no engagement rings), per-person material-connection disclosure lines per FTC and 《互联网广告管理办法》, and a Slack/Teams distribution spec. Not for paid creator campaigns — use campaign-planner. 员工倡导/创始人IP分享/内部分享计划/披露合规
Harmonize multiple Blender skills into a coherent pipeline with clear activation precedence, handoff artifacts, dependency gates, and conflict-resolution rules. Use when a Blender task spans several skills, when reference-locked work conflicts with generic production workflow, after adding/updating skills, or when repeated failures indicate skill interference or missing inter/intra-play.
Network flow analysis in Dynatrace across three sources: OneAgent flows (host/process/pod-to-peer connections in the `default_network_flows` Grail bucket), NetFlow/IPFIX/sFlow (via an OpenTelemetry Collector), and cloud flow logs (AWS VPC / Transit Gateway; Azure and GCP planned). Use to analyze traffic between entities, find top talkers by bandwidth, map communication dependencies, investigate connection health (resets, timeouts, retransmissions, RTT), and resolve peers to monitored entities. Routes each question to the right source; source-specific DQL lives in the reference files. Trigger: "network flows", "top talkers", "traffic between hosts", "connection resets", "TCP retransmissions", "RTT", "pod connections", "network dependencies", "NetFlow", "IPFIX", "sFlow", "VPC flow logs", "cloud network traffic". Do NOT use for host NIC throughput or packet drops (use dt-obs-hosts), service request rate or latency (use dt-obs-services), or synthetic/uptime monitoring (use dt-obs-ext-monitors).
Use when the user asks to "personalize the email", "add merge tags / dynamic content", "set up conditional blocks per segment", or "make first-name and product-recommendation fields fall back safely"; produces a merge-tag map with per-tag fallbacks, conditional-block rules with per-segment variations, a fallback-safety audit, and a PII guard on what may render, informing the SEND E (Engagement/personalization) dimension. Not for building the segments — use list-segment-builder; not for writing the base copy — use email-creative-builder; not for scoring EQS or running vetoes — use email-quality-auditor. 邮件个性化/合并标签/条件内容块/兜底默认值
Build accretion/dilution analyses for M&A transactions. Model pro forma EPS impact, synergy sensitivities, and purchase price allocation. Use when evaluating a potential acquisition, preparing merger consequences analysis for a pitch, or advising on deal terms. Triggers on “merger model,” “accretion dilution,” “M&A model,” “pro forma EPS,” “merger consequences,” or “deal impact analysis”
Use when the user asks to "author our durable brand message hierarchy", "build the brand message house that seeds the canon", or "define the main narrative, three pillars, and tagline for the whole brand"; produces the DURABLE brand message system — main narrative, three value pillars, per-persona proof points (each labeled Measured / User-provided / ''[needs source]''), and the tagline/one-liner — that seeds the narrative-registry canon and from which every per-launch house derives. Not for a single launch''s message house or PR-FAQ — use message-house-builder; not for claim adjudication — use offer-claims-registry; not for the change-narrative arc itself — use strategic-narrative-designer. 品牌消息屋/主叙事/三支柱/标语/持久叙事 canon
Use when the user asks to "build our social posting calendar", "set weekly slots and queue depth per channel", or "plan the evergreen recycle rotation"; produces the always-on brand calendar — pillar allocation with hero/hub/help balance and give:ask targets (all labeled Estimated starting heuristics to calibrate against own analytics, never scored rules), per-channel recurring slots with queue depth, a batching workflow, an evergreen recycle cycle with freshness re-checks, deliberate open slots for realtime/trend moments fed by trend-spotter go/skip verdicts, and first-comment/publish-order ops — cadence commitments filed to the channel registry, and no batch ships to the queue without a SHIP verdict from social-quality-auditor pre-publish mode. Not for repurposing an existing asset or the paid-amplification calendar — use content-amplifier. 社媒排期/内容日历/栏目配比/常青循环复用
Use when the user asks to "set up my founder social-selling routine", "build a daily engagement block for target accounts", or "turn funding / hiring signals into selling plays"; produces the founder/seller daily operating block — a time-boxed engagement-block spec (substantive value-add comments on target-account posts, never a pitch), warm-touch-before-ask cadence rules, trigger-response plays consuming the social-pulse-monitor B2B trigger watchlist (funding / hiring / launch signals), and a quarterly diagnostic that reads LinkedIn SSI as an input diagnostic only (Estimated, vendor-defined — never a target metric). All volume norms are Estimated/community-derived; all execution is human — zero mass-DM, zero connection-request automation, zero engagement automation (LinkedIn UA §8.2 red line); 1:1 pitch and DM mechanics route to outreach-manager. Not for cold email sequences — use cold-outbound-sequencer. 社交销售/创始人日常互动块/热身触达节奏/触发信号剧本
Transcribe audio to text with ElevenLabs Scribe and Whisper models via inference.sh CLI. Models: ElevenLabs Scribe v2 (98%+ accuracy, diarization), Fast Whisper Large V3, Whisper V3 Large. Capabilities: transcription, translation, multi-language, timestamps, speaker diarization, audio event tagging. Use for: meeting transcription, subtitles, podcast transcripts, voice notes. Triggers: speech to text, transcription, whisper, audio to text, transcribe audio, voice to text, stt, automatic transcription, subtitles generation, transcribe meeting, audio transcription, whisper ai, elevenlabs stt, scribe, eleven labs transcribe
Plans, executes and documents validation, verification and transfer of analytical procedures under the governing framework — ICH Q2(R2) and Q14, USP <1220>/<1225>/<1226>, ICH M10 bioanalytical, CLSI EP or ISO/IEC 17025. Use for HPLC, LC-MS/MS, GC, CE, ICP-MS, dissolution, qNMR, qPCR, NIR and ligand binding or cell-based assays whenever the question is whether a procedure is fit for its intended purpose. Triggers include "method validation", "analytical method validation", "AMV", "validation protocol", "acceptance criteria", "linearity", "reportable range", "accuracy and precision", "repeatability", "intermediate precision", "recovery", "LOD", "LOQ", "detection limit", "quantitation limit", "specificity", "robustness", "method transfer", "method comparison", "Deming", "Passing-Bablok", "Bland-Altman", "equivalence testing", "OOS investigation", "ICH Q2", "Q2(R2)", "Q14", "USP 1225", "ICH M10", "incurred sample reanalysis", "ISR", "CLSI EP", and any request to show that an assay works.
Use to build a content calendar — a sustainable, repeatable posting rhythm and recurring structure (which pillars/formats post on which days, on which platforms), derived from strategy and pillars. Run when the user says "content calendar," "editorial calendar," "social media calendar," "posting schedule," "content plan" (ongoing), "what should I post each week," "build me a posting routine/cadence," or wants a repeatable system rather than one period's posts. Reads social-strategy, content-pillars, and brand-profile first; sizes cadence to real capacity; builds a recurring skeleton of buckets and named series with room reserved for reactive/trend content; sets the planning rhythm (batch, buffer, review). Hands a period's briefs to batch-content-plan, content to the writing skills, and scheduling to scheduling-and-queue. For filling one specific week/month with actual posts use batch-content-plan; for higher-level channel/goal choices use social-strategy.
Entrypoint for AI coding assistant rule authoring across GitHub Copilot, Cursor, and Claude Code. USE FOR: setting up rules, reviewing existing rules, scaffolding instruction files, or asking which editor format to use. DO NOT USE FOR: authoring skills (SKILL.md), agent definitions (.agent.md), or CI enforcement of rule files.
Install and operate Grimoire, author .spell files with full syntax coverage (including advisory decision logic), and run compile/validate/simulate/cast safely. Use when users ask to create, edit, debug, validate, simulate, execute, or explain Grimoire strategies.
Use when the user asks to "track where my emails are actually landing after I send", "read my seed-list inbox vs spam vs promotions results", "trend my Gmail Postmaster / Microsoft SNDS reputation", or "did placement drop after my last send"; produces a per-provider inbox/spam/promotions placement read, a domain/IP reputation trend from Postmaster + SNDS, a send-over-send delta with named regressions, and a reusable SEND-S placement snapshot on your own exported telemetry. Not for the pre-send SPF/DKIM/DMARC auth pre-flight — use deliverability-qa; not for computing the EQS or running the vetoes — use email-quality-auditor. 邮件收件箱落点监测/收件箱vs垃圾邮件/Postmaster声誉趋势
Use when the user asks to "audit our launch plan", "are we ready to launch", or evaluate launch execution/outcomes; runs one typed RAMP preflight, execution, or outcome profile without mixing time horizons. Not for recording launch state — use launch-registry; not for running launch day — use launch-day-conductor. 发布就绪审计/RAMP分阶段评估/发布前放行
Use when the user asks to “build email segments from my list”, “make engaged / lapsed / RFM segments”, “set up cart-abandoner or lifecycle-stage audiences”, or “build a suppression list of unsubscribes and bounces”; turns the user's OWN list/CRM/GA4/ecommerce export into behavioral, attribute, and lifecycle-stage segments plus a suppression list, with per-segment sizes labeled Measured/Estimated, informing the SEND E (Engagement/targeting) dimension. Not for scoring EQS or running vetoes — use email-quality-auditor; not for authentication or spam-content checks — use deliverability-qa. 邮件列表分群/生命周期分群/抑制名单/流失召回
When the user wants to run native ads on Taboola, Outbrain, or similar platforms. Also use when the user mentions “native ads”, “Taboola”, “Outbrain”, “content recommendation”, “sponsored content”, or “in-feed ads”. For strategy, use paid-ads-strategy.
When the user wants to optimize videos for Google Search, video sitemap, VideoObject schema, or video SEO on websites. Also use when the user mentions "video SEO," "video sitemap," "VideoObject," "video thumbnail," "video indexing," "video preview," "key moments," "Clip schema," or "embedded video optimization." For page template, use article-page-generator.
Downloads, exports, and inspects existing Arize traces and spans to understand what an LLM app is doing or debug runtime issues. Covers exporting traces by ID, spans by ID, sessions by ID, and root-cause investigation using the ax CLI. Use when the user wants to look at existing trace data, see what their LLM app is doing, export traces, download spans, investigate errors, or analyze behavior regressions
Search products across Chinese e-commerce platforms: Taobao, Tmall, XHS (小红书). Zero-config — no API keys needed. Powered by Shopme unified product database. Use when the user asks to find products, get product info by URL or ID, search Chinese suppliers, or compare prices.
Use when the user asks to "set up conversion values so tROAS optimizes profit not orders", "map margin onto my purchase value", "build value rules for lead / phone / signup conversions", or "stop bidding to revenue when I care about profit"; defines and QAs the conversion VALUE model — per-conversion values, margin/net-value adjustment, static-vs-dynamic value rules, proxy values for non-revenue actions, and a value-vs-count sanity check — as a value-model spec plus a pre-launch value QA sheet. Not for whether the tag fires or UTMs are clean — use conversion-signal-qa; not for cross-platform double-count de-dup — use attribution-reconciler; not for scoring R1/R2 — that is a scored veto in ad-account-auditor. 付费广告转化价值建模/利润出价/价值规则QA
Use when the user asks to “grow my email list”, “design a lead magnet / signup incentive”, “set up double opt-in”, or “plan a referral / recommendation loop”; produces a list-growth plan — acquisition channels, lead-magnet / incentive concepts, a compliant double-opt-in capture-flow spec, referral-loop mechanics, and subscriber-growth / cost-per-opt-in targets (labeled Estimated) — that feeds SEND-S (consent quality captured at acquisition) and SEND-N (lifecycle entry). Not for the signup page/popup UX itself — use landing-optimizer; not for recording the opt-in — use consent-registry; not for the confirmation-email copy — use email-creative-builder. 邮件列表增长/lead magnet/双重确认/推荐环
Use when the user asks to "plan launch pricing", "design pricing tiers / packaging", or "set up a launch discount / early-bird offer"; produces a launch pricing and packaging plan — tier structure and naming, a value-to-price map aligned to the message house, a launch-offer ladder with a true deadline reason, beta / early-adopter pricing with a post-launch graduation path, and guarantee / refund terms — with every price claim and offer term submitted to memory/events/claims.ndjson. Not for the canonical offer / claim record — use offer-claims-registry; not for paid-newsletter subscription economics — use newsletter-monetization-planner; not for ad bidding — use bid-strategy-planner. 发布定价/梯度打包/早鸟优惠/保证设计
Compares an app clone against the original: a feature parity score from the feature matrix (weighted by must, should, could) with the missing list in build order, plus a screenshot layout diff that ignores colour so a rebrand does not count against you. Two standard-library Python tools. Use when the user says "how close is my clone", "compare it to the original", "what's missing", "parity check", "diff the screens", "is it ready", or after /replica-test.
Use when the user asks to "build a story bank", "collect our origin and customer stories", or "assemble reusable proof stories for the message"; assembles reusable narrative units — origin, founder, customer, transformation, and proof stories — each tagged to a claims-ledger ID and a message-house pillar, with every proof labeled Measured / User-provided / [needs source]. Not for authoring the message house or pillars — use message-system-architect; not for brand voice or naming rules — use brand-language-codifier; not for finished long-form prose — use content-writer; not for adjudicating whether a proof is true — use offer-claims-registry. 品牌故事库/起源客户转化/证据故事单元
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.