「token」の検索結果

Generate a complete component file tree wired to design tokens with tests and Gherkin spec. Use when scaffolding a new UI component.

日本語の概要は準備中です。原文の説明を表示しています。

Produce a coherent visual identity (palette, typography, spacing, radius) from a brief and serialise to JSON for the design-tokens skill. Use when establishing brand identity.

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Set up Hierarchical Agent Memory (HAM) — scoped CLAUDE.md files per directory that reduce token spend. Trigger on "go ham", "set up HAM", "ham commands", "ham help", "ham route", "ham remove", "ham update", "ham status", "ham benchmark", "ham baseline start", "ham baseline stop", "ham metrics clear", "HAM savings", "HAM stats", "HAM dashboard", "HAM sandwich", "HAM insights", "HAM carbon", or "ham sync".

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Intercept and debug Claude Code API requests using mitmproxy. Inspect system prompts, tool definitions, token usage, and streaming responses. Triggers: cc-trace, mitmproxy, API interception, Claude Code debugging, traffic inspection.

日本語の概要は準備中です。原文の説明を表示しています。

Deploy serverless applications on Cloudflare Workers. Covers project setup, JavaScript handler patterns, routing, deployment with Wrangler, and API token configuration. Suitable for APIs, proxies, edge computing, and request transformation.

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Interact with Bitbucket repositories and pull requests using the BITBUCKET_TOKEN environment variable. Use when working with code hosted on Bitbucket or managing Bitbucket resources via API.

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CatColab Petri Nets - concurrent system modeling via places (states), transitions (events), and token flow. Foundation for process algebra, workflow, and chemical reaction networks.

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Interact with Azure DevOps repositories, pull requests, and APIs using the AZURE_DEVOPS_TOKEN environment variable. Use when working with code hosted on Azure DevOps or managing Azure DevOps resources.

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Interact with Axiom.trade -- a Y Combinator-backed (W25) DEX aggregator and trading platform on Solana with Hyperliquid perpetuals integration. Covers API architecture, multi-wallet management, MEV protection, token discovery, and wallet tracking.

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Interact with Aptos blockchain - check balances, transfer APT, swap tokens, stake, and execute Move view functions. Features game-theoretic decision analysis with Nash equilibrium detection. All transactions require explicit approval.

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Configures CI/CD pipelines for automated Python package publishing to PyPI or GitLab Package Registry. Use when creating GitHub Actions or GitLab CI release workflows, setting up trusted publishing or API token-based PyPI authentication, configuring version management with git tags and hatch-vcs, writing pyproject.toml publishing metadata, testing packages against TestPyPI, or documenting the release process for a Python project.

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Assess and refactor oversized or multi-domain skills. First determines whether splitting or references/ extraction is appropriate — then executes the correct action. Use when a skill exceeds token thresholds (SK006/SK007) or covers multiple independent domains. Performs candidate assessment before any structural changes; cohesive single-intent skills are redirected to references/ extraction instead of splitting. When splitting is warranted — domain analysis gate, split plan, new SKILL.md generation, validation, and backwards-compatible facade conversion.

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Integrate MCP servers into Claude Code plugins — covers .mcp.json configuration, plugin.json mcpServers field, server types (stdio, SSE, HTTP, WebSocket), environment variable expansion, tool naming conventions, OAuth and token authentication, security best practices, and testing workflows. Use when adding an MCP server to a plugin, configuring MCP authentication, debugging MCP tool discovery, setting up Model Context Protocol integration, or choosing between stdio and SSE transport types.

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Optimize existing CLAUDE.md, SKILL.md, agent definitions, and other AI-facing files for Claude comprehension and economy. Scope: optimization of existing content only — not upstream sync, not read-only auditing. Measures baseline metrics, delegates to the ai-doc-optimizer agent with file-type-specific context, runs independent verification via second agent, measures post-optimization metrics, and presents comprehensive before/after report. Supports iterative mode for large targets. Use when improving prompt effectiveness, reducing token waste, or rewriting instructions for LLM consumption. Invoke with /optimize-claude-md <file-or-directory>.

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Use when checking skill quality, validating frontmatter before commit, or diagnosing validator warnings. Runs the plugin validator on a skill, agent, or plugin directory — reports token complexity, broken links, frontmatter issues, and structural problems. Pass the path as an argument.

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Reviews LLM integration, prompt templates, model selection, token/cost budgets, evaluation harnesses, structured outputs, retries, and streaming. Checks trust boundaries and task evidence against the selected provider/model contract rather than prescribing universal model tiers or sampling settings.

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Install and configure the GitHub CLI (gh) for AI agent environments where gh may not be pre-installed and git remotes use local proxies instead of github.com. Use when gh command not found, shutil.which returns None, need GitHub API access for issues or PRs or releases or workflow runs, or repository operations fail with 'failed to determine base repo' error. Provides auto-install script with SHA256 verification, GITHUB_TOKEN auth with anonymous fallback, and the required -R flag pattern for proxy environments. Covers project management via GitHub Projects V2, milestones via REST API, issue lifecycle templates, and label taxonomy management.

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Reads a model's own uncertainty from token log-probabilities: collecting and aggregating label logprobs, confidence tiers and margins for triage, calibration against human labels (ECE, Brier, reliability diagrams), downstream use, and reproducibility. Use for per-item classifier confidence or routing low-confidence cases to human review; codebook and validation design go to text-classification.

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How to use Figma MCP and Variables2CSS to read designs from Figma and generate code consistent with tokens. Use when the designer shares a Figma link.

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[AUTO-INVOKE] MUST be invoked BEFORE deploying DeFi contracts (DEX, lending, staking, LP, token). Covers anti-whale, anti-MEV, flash loan protection, launch checklists, and emergency response. Trigger: any deployment or security review of DeFi-related contracts.

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Check a text fragment for potential secrets (API keys, tokens, passwords) BEFORE sending to chat / committing / publishing. Second protection layer on top of the pre-commit hook — manual gate, user explicitly calls on potentially sensitive text.

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Build stateful AI agents using the Cloudflare Agents SDK. Load when creating agents with persistent state, scheduling, RPC, MCP servers, email handling, or streaming chat. Covers Agent class, AIChatAgent, state management, and Code Mode for reduced token usage.

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Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling. JSON Schema best practices, description writing that actually helps the LLM, validation, and the emerging MCP standard that's becoming the lingua franca for AI tools. Key insight: Tool descriptions are more important than tool implementa

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Real-time cost tracking, budget enforcement, and ROI measurement for AI agent operations. Track token usage, predict costs, enforce budget caps ($50-70/month typical), optimize model selection, cache results, measure cost-to-value. Use when tracking AI costs, preventing budget overruns, optimizing spend, measuring ROI, or ensuring cost-effective AI operations.

日本語の概要は準備中です。原文の説明を表示しています。