From radar
Combined scan + recommend pipeline. Scans external sources for new AI tools and techniques, then matches them against your goals and usage patterns to surface personalized recommendations.
npx claudepluginhub flippyhead/radar --plugin radarThis skill uses the workspace's default tool permissions.
Combined scan + recommend pipeline. Scans external sources for new AI tools and techniques, then matches them against your goals and usage patterns to surface personalized recommendations.
Searches, retrieves, and installs Agent Skills from prompts.chat registry using MCP tools like search_skills and get_skill. Activates for finding skills, browsing catalogs, or extending Claude.
Searches prompts.chat for AI prompt templates by keyword or category, retrieves by ID with variable handling, and improves prompts via AI. Use for discovering or enhancing prompts.
Guides TDD-style skill creation: pressure scenarios as tests, baseline agent failures, write docs to enforce compliance, verify with RED-GREEN-REFACTOR.
Combined scan + recommend pipeline. Scans external sources for new AI tools and techniques, then matches them against your goals and usage patterns to surface personalized recommendations.
This is the default entry point. Use /radar-scan or /radar-recommend separately if you need different scheduling cadences (e.g., scan daily, recommend weekly).
$ARGUMENTS — Optional:
--days N — Lookback window for both scan and recommend (default: 7 for scan, 14 for recommend)--sources <all|feeds|manual> — Source filter for scan phase (default: all). "feeds" = structured external sources (Anthropic, HN, GitHub, YouTube, dependency changelogs). "manual" = process user-added inbox items only.--focus <category> — Category filter for recommend phase (claude-code, mcp, api, agent-sdk, prompting, tooling, workflow, general-ai)Parse from $ARGUMENTS if provided.
Execute the full /radar-scan workflow with the --sources and --days arguments.
Print a brief summary of scan results (new items catalogued, notable finds) before proceeding.
Execute the full /radar-recommend workflow with the --days and --focus arguments.
This phase uses the freshly updated catalogue from Phase 1, ensuring recommendations reflect the latest scan.
Output a combined summary: