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Found 174 Skills
Cluster and attribute related wallets — funding chains, shared signers, CEX deposit patterns. Use when tracing wallet ownership, governance voters, or related address clusters.
Performance playbook for `weapp-vite + wevu` mini-program projects, aligned with WeChat runtime guidance (`setData`, render, navigation, resource, memory). Use this whenever users report lag, frame drop, white screen, slow page switching, memory alert, or want to implement systematic performance governance, stress testing and regression.
ALWAYS invoke this skill at the START of every session before doing any other work. Validates project health: governance rules, tool availability, memory directory, settings files, script permissions, .agents directory, and .beads/.gitignore hygiene. Remediates issues across all swain skills. Idempotent — safe to run every session.
Build and grow online communities across all platforms and contexts — from developer/B2B communities (Discord, Slack, Circle, Discourse) to social communities (Twitter/X, Reddit, Farcaster) to crypto/holder communities (Telegram). Covers strategy, platform selection, channel architecture, member journey mapping, onboarding, engagement rituals, ambassador/champions programs, moderation, governance, growth, retention, crisis management, and metrics. Use for: community-led growth, community strategy, developer community, user community, Discord/Slack/forum/Telegram setup, ambassador programs, community health, holder psychology, engagement systems, social community building, cross-platform coordination.
One-time project onboarding for swain. Migrates existing CLAUDE.md content to AGENTS.md (with the @AGENTS.md include pattern), verifies vendored tk (ticket) for task tracking, configures pre-commit security hooks (gitleaks default), and offers to add swain governance rules. Run once when adopting swain in a new project — use swain-doctor for ongoing per-session health checks.
Screen and analyze stocks through an ESG (Environmental, Social, Governance) lens, evaluating sustainability practices, controversy exposure, and responsible investing criteria. Use when the user asks about ESG investing, sustainable investing, socially responsible investing (SRI), impact investing, green stocks, carbon footprint analysis, governance quality assessment, controversy screening, exclusion lists, or ESG scoring of companies or portfolios.
Analyzes events through indigenous knowledge systems using relational thinking, seven generations principle, reciprocity, holistic integration, and traditional ecological knowledge frameworks. Provides insights on interconnectedness, long-term sustainability, collective wisdom, and decolonial perspectives. Use when: Environmental decisions, resource stewardship, community governance, decolonization, intergenerational planning. Evaluates: Relationships, sustainability, collective impact, indigenous rights, traditional knowledge integration.
World-class design systems architecture - tokens, components, documentation, and governance. Design systems create the shared language between design and engineering that makes products feel cohesive at any scale. Use when "design system, component library, design tokens, atomic design, style guide, theme, theming, design scale, component api, variant, figma tokens, style dictionary, design-system, tokens, components, theming, documentation, figma, accessibility, versioning" mentioned.
Build a Community Building Pack (strategy, platform plan, programming calendar, ambassador program, governance, metrics, launch plan). Use for community building, community-led growth, developer community, user community, ambassador/champions programs, Discord/Slack/forum communities. Category: Marketing.
Audit GitHub repository branch governance and workflow hygiene. Use when asked to review rulesets, required status checks, update restrictions, delete-on-merge settings, auto-merge workflow reliability, stale branches, ghost workflow registrations, or branch-policy drift.
Strategic guidance for operationalizing machine learning models from experimentation to production. Covers experiment tracking (MLflow, Weights & Biases), model registry and versioning, feature stores (Feast, Tecton), model serving patterns (Seldon, KServe, BentoML), ML pipeline orchestration (Kubeflow, Airflow), and model monitoring (drift detection, observability). Use when designing ML infrastructure, selecting MLOps platforms, implementing continuous training pipelines, or establishing model governance.
Use when defining events, fields, and governance for GTM analytics pipelines.