Results for “discovery-api”

Manage Notion workspace: search pages and databases, read markdown, create pages, insert rows, triggers, MCP. Powered by AISA gateway (Notion toolkit). Requires AISA_API_KEY and curl. Keywords: notion, workspace, page, database, block, markdown, wiki, task board, insert row, OAuth. Use when: the user needs web search, research, source discovery, or content extraction.

Use this skill when a user asks for SEO keyword research, keyword discovery, search volume analysis, keyword difficulty, search intent mapping, topic clusters, content opportunities, competitor keyword gaps, or a keyword strategy for a domain, URL, product, market, or seed topic. When a website is provided, crawl and interpret the site first, then use AIsa API access to DataForSEO keyword, SERP, trend, Labs, and OnPage endpoints plus AIsa LLM reasoning to find non-brand keyword opportunities. Use when: the user needs web search, research, source discovery, or content extraction.

Use when building, refactoring, or documenting Graft apps and proxies, including when asked to create a tool server, API server, dual-protocol server, or MCP-HTTP bridge. Graft's core thesis: define tools once and serve them as both HTTP REST endpoints and MCP tools from the same server, with discovery, docs, and OpenAPI generated automatically. Covers concrete actions such as defining tools and handlers, configuring authentication middleware, setting up HTTP and stdio transports, generating OpenAPI documentation, wrapping existing APIs via proxy mode, and wiring up the full CLI workflow.

Onboard AI agents into the Senpi trading platform on Hyperliquid. Walks through account creation, API key setup, MCP server configuration, skill discovery, and first-trade guidance. Includes a mandatory skill update check that surfaces new or updated skills after onboarding. Use when user says "set up Senpi", "get started with Senpi", "connect to Senpi", "install Senpi", "onboard to Senpi", or when an agent needs to start trading on Hyperliquid via Senpi.

Fast, accurate code search for AI agents using ~98% fewer tokens than grep+read. Indexes any local or remote repository in under a second (~250ms on CPU, no GPU or API key needed). Supports natural-language and symbol queries, semantic similar-code discovery, and MCP server integration for Claude Code, Codex, Cursor, and OpenCode. Python library available for programmatic use. Triggers on: semble, code search, semantic code search, semble search, token-efficient search, find code, code search mcp, agent code search, semble find-related, semble savings.

Designs the contract for an API change inside one codebase — a component's props, a function surface, URL or query parameters, an event payload, or a module boundary — through a discovery pass, an options document with one recommendation, a question round, and an adversarial validation round, with every element of the contract justified from one stated goal. Use when you want to design, shape, decide, or nail down an interface, contract, signature, or API change for a capability you can already describe, sized for roughly one pull request. Produces a design document and changes no code. Does not specify what a feature should do — use plan-a-feature. Does not plan delivery or sequencing — use plan-implementation. Does not assess the architecture of existing code — use architectural-analysis. Does not write the code — use tdd. Does not restructure existing code — use refactor. Runs its rounds without pausing for review; to review each round as it lands, use pairing.