AI & ML Agent Skills

Best practices for using the oracle CLI (prompt + file bundling, engines, sessions, and file attachment patterns).

Install and use the official Stripe Claude Code plugin (stripe@claude-plugins-official), connect Stripe MCP (mcp.stripe.com), and implement modern Stripe payments with Checkout Sessions, PaymentIntents, SetupIntents, and Billing — never legacy Charges. Use when building Stripe checkout, subscriptions, webhooks, Connect, restricted keys, test cards, or running /plugin install stripe@claude-plugins-official / /explain-error / /test-cards.

For questions about Light Protocol's SDK, smart contracts and Solana development, Claude Code features, or agent skills. AI-powered answers grounded in repository context via DeepWiki MCP.

Clawdex — dual-engine coding agent. Claude Code (reasoning + planning) + OpenAI Codex (fast execution) + Browser Use boxes (web research) + Upstash compute boxes (isolated sandboxes).

This skill should be used when the user wants to "dca into" a token, "buy X every day", set up a "recurring buy", "dollar cost average" into an asset, "schedule a buy", or "auto-buy on a dip". Buys a fixed amount into a token on a schedule, optionally only when a condition holds (for example only when ETH is below a price threshold). The host agent's scheduler wakes the skill on a cadence; each wake is one self-contained run.

Compact the current conversation into a handoff document for another agent to pick up.

Entry-point router for the local Pump.fun skill suite. Use when the user asks about launching Pump.fun tokens, bonding-curve or AMM trading, quotes, fees, claims, incentives, SDK work, agent/MCP integration, security, testing, or release workflows.

Use the ClawdHub CLI to search, install, update, and publish agent skills from clawdhub.com. Use when you need to fetch new skills on the fly, sync installed skills to latest or a specific version, or publish new/updated skill folders with the npm-installed clawdhub CLI.

Use the mcporter CLI to list, configure, auth, and call MCP servers/tools directly (HTTP or stdio), including ad-hoc servers, config edits, and CLI/type generation.

Self-hosted OpenAI-compatible LLM router — smart tier-based routing, ZK-stamped routing decisions, mode overrides, free OpenRouter at install via the Birth bot. Save 60-80% on inference costs by routing to the cheapest capable model across 12+ OpenRouter models.

Discover and use DFlow documentation, Agent CLI, Trading API, Metadata API, Proof KYC, prediction markets, and the hosted DFlow docs MCP. Use before implementing DFlow features or when field-level endpoint details are needed.

Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.

Pay HTTP 402 payment challenges issued by OKX's Agent Payments Protocol (APP) on X Layer using tokens from any chain via the Uniswap Trading API. Use this skill whenever the user encounters a 402 challenge whose network resolves to X Layer (chain 196), mentions "APP", "Agent Payments Protocol", "OKX agent payment", "OKX Onchain OS", "OKX agentic wallet", "x402 on X Layer", "USDT0", "x42", "Instant Payment", "Batch Payment", "pay for X Layer API", or wants to pay an OKX-backed merchant. Even when the user does not explicitly say APP, prefer this skill for any 402 challenge whose network resolves to X Layer (chain 196). For 402 challenges on other chains (Ethereum, Base, Arbitrum, Tempo) use pay-with-any-token instead.

Cheshire Skills Store index — curated Agent Skills packages for Cheshire Terminal (API, PostHog, Google Agent Registry, Skill Hub onchain, Stripe, Solana common errors, NOXA) plus the community skills collection. Use when installing store skills, browsing the store catalog, or wiring cheshireterminal.ai/skills-store.

One-shot setup and operation guide for the solana-clawd agentic engine. Use when: cloning the repo, setting up MCP tools, starting the Telegram bot, deploying to Fly.io/Netlify, hatching blockchain buddies, running OODA loops, configuring voice mode (ElevenLabs + Grok), minting Metaplex agents, managing the vault, running the worker swarm, or contributing to the project. Covers all 31 MCP tools, 18 buddy species, 9 spinners, 60+ Telegram commands, 95 skills, and the full repo structure.

Use the host-side `agent-browser` CLI for local browser smoke tests, screenshots, snapshots, and simple UI validation against forwarded localhost URLs.

Interactive QA session where user reports bugs or issues conversationally, and the agent files GitHub issues. Explores the codebase in the background for context and domain language. Use when user wants to report bugs, do QA, file issues conversationally, or mentions "QA session".

Walk through the manual-capture.md checklist for a slug, driving Chrome via the Claude in Chrome MCP to capture each visual that needs more than a static URL — multi-step flows, conversation states, settings panels, age gates on third-party sites. Runs equally well locally (your desktop Chrome) or on a VPS with always-on Chrome + the extension installed. Defaults to unattended mode when `BLOG_AGENT_AUTONOMOUS=1` (which forces `UNATTENDED=1`). Use after /generate-visuals has flagged action-shot or failed-screenshot entries.

Execute a relaunch on a decayed-but-valuable article (Lesson 5 audit + Lesson 8 "don't abandon old winners"). Take a page the audit flagged as decaying or rank-slipping, refresh it against the LIVE SERP (freshen data, re-verify searcher intent, squeeze new keywords, refresh visuals), bump its published date, and re-promote it as if brand new. The "update ~half the calendar" half of the strategy. Triggered from the audit's Relaunch plan.

Craft Higgsfield-grade, hyper-structured image-generation prompts for every blog visual. MANDATORY before any image generation call (generate-visuals, Replicate, GPT-Image, Nano Banana). A weak one-line prompt is a gate failure — every [VISUAL] placeholder gets a full structured prompt built with this skill first.

Linkable-Asset Skill — data studies that pull links (Lesson 7)

Post-draft pass that expands a drafted article to capture the FULL keyword family — keywords the page already or could rank for, plus the Ahrefs Content Gap (keywords competitors rank for but we don't) — by weaving the worthwhile ones in as natural added paragraphs/sections. NOT keyword stuffing. Triggered after /draft, before /quality-check.

Off-page playbook (Lesson 9, link building). Mines our competitors' backlink profiles via Ahrefs to produce a VETTED link-prospect list — their "superfans" (sites linking to several of a competitor's best-by-links pages), their "power-linkers" (sites linking to multiple competitors but NOT to us), and their fresh new links — filtered for relevance and de-duped against sites that already link to us. The Link Intersect method, encoded. Output is a prospect queue for /outreach; it does NOT send anything.

After any AI-generated explanation, require the learner to identify one place it could be wrong, one thing to check, and one source to consult. Builds epistemic vigilance — treats AI output as a claim to evaluate, not truth to absorb.

Seven-role depersonalised panel review of framework artefacts (KUD, criterion bank, LT definition, crosswalk, scope-and-sequence) in sequential-isolation mode. Gate rule mean>=88 AND no role<70.

Wrap a learning session in a plan → monitor → reflect cycle. Use at the start of any substantial study session to set goals, mid-session to check strategy, and at session end to consolidate what changed. Builds self-regulated learning as a habit.

Surface beliefs, assumptions, stories, and values shaping a system. Use when deeper mental models need examining with care and evidence.

Authors or reviews Know/Understand/Do charts for competency-based learning targets across developmental bands. Handles seven input types from raw curriculum documents to existing LT sets. Routes to upstream skills when stronger inputs are available.

Review the week using accumulated session evidence — retrieval rates, hint depths, calibration accuracy, transfer and unassisted results. The learner identifies patterns and sets a strategy goal. Use weekly or after a multi-session period.

Map which elements of an assignment benefit from AI assistance vs. which AI use undermines. Use when redesigning tasks for AI-age classrooms or setting defensible AI use policies for specific assignments.

Predicts access barriers in a learning task before delivery, given a learner variability profile. Distinguishes between barriers addressable through design and those requiring specialist support.

Compares two or more band-tagged frameworks and produces a framework-neutral topic matrix showing coverage and gaps across all inputs, plus an optional reference-centric PLC crosswalk document when a reference framework is supplied.

Unpack a broad standard or competency descriptor into specific, assessable success criteria and sub-skills. Use when interpreting curriculum standards or writing learning objectives.

Build students' capacity to interrogate a historical source before reading — asking who authored it, when, why, and what this means for reliability. Use when students read documents without attending to authorship.

Require the learner to explain a concept in their own words before the AI evaluates or extends it. Ensures the AI works from the learner's understanding rather than providing an explanation from scratch.

Design a project-based learning brief with a driving question, milestones, and assessment criteria. Use when planning PBL units, inquiry projects, or extended investigations.