aria_skills/browser/SKILL.md
# aria-browser — Headless Browser Skill **Layer:** 2 (Infrastructure) | **Category:** Browser | **Status:** Active ## Purpose Headless browser access via the `aria-browser` (browserless/chromium) service. Navigate, snapshot, screenshot, and scrape web pages without needing a local browser binary. ## Configuration (env vars) | Variable | Default | Description | |----------|---------|-------------| | `BROWSERLESS_URL` | `http://aria-browser:3000` | Browserless service URL | | `BROWSERLESS_INT
npx skillsauth add najia-afk/aria_moltbot aria_skills/browserInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Layer: 2 (Infrastructure) | Category: Browser | Status: Active
Headless browser access via the aria-browser (browserless/chromium) service. Navigate, snapshot, screenshot, and scrape web pages without needing a local browser binary.
| Variable | Default | Description |
|----------|---------|-------------|
| BROWSERLESS_URL | http://aria-browser:3000 | Browserless service URL |
| BROWSERLESS_INTERNAL_PORT | 3000 | Internal container port (used for URL construction) |
| Tool | Description |
|------|-------------|
| navigate(url, wait_for?, timeout?) | Fetch full page HTML, title, and HTTP status |
| snapshot(url, selectors?) | Structured page extract: title, headings, links, meta, text |
| screenshot(url, full_page?) | Capture PNG as base64 |
| scrape(url, elements[]) | Extract specific elements by CSS selector |
# Via run_skill.py
python3 aria_mind/skills/run_skill.py browser navigate '{"url": "https://example.com"}'
python3 aria_mind/skills/run_skill.py browser snapshot '{"url": "https://example.com"}'
# Via aria agent tools
aria-browser.navigate({"url": "https://example.com"})
aria-browser.scrape({"url": "https://example.com", "elements": [{"selector": "h1"}]})
httpx — HTTP client for browserless APIaria-browser Docker service (browserless/chromium v2)browserless/chrome v1 → ghcr.io/browserless/chromium v2 in S-50navigate for full HTML; use snapshot for structured content (lower token cost)tools
# aria-working-memory Persistent short-term memory operations for Aria runtime context. ## Purpose - Store, retrieve, rank, checkpoint, and prune working memory. - Provide high-relevance context for decision and response flows. ## Main Tools - `remember` - `recall` - `get_context` - `checkpoint` - `restore_checkpoint` - `forget` - `update` - `reflect` - `sync_to_files`
development
```skill --- name: aria-unified-search description: "🔎 RRF-merged search across semantic + graph + memory backends" metadata: {"aria": {"emoji": "🔎"}} --- # aria-unified-search Unified search engine that queries semantic memories (pgvector cosine), knowledge graph (ILIKE), and traditional memories (text match), then merges results via Reciprocal Rank Fusion (RRF) with content-hash deduplication. ## Architecture ``` Query ↓ (parallel to 3 backends) ├── SemanticBackend (pgvector cosi
tools
# aria-telegram Telegram Bot API integration skill. ## Purpose - Send and reply to messages through bot credentials. - Fetch updates and basic bot metadata. ## Main Tools - `send_message` - `reply_to_message` - `get_updates` - `get_me`
tools
# aria-sprint-manager Sprint planning and board flow management skill. ## Purpose - Operate goal board as Product Owner. - Move, prioritize, and report sprint progress. ## Main Tools - `sprint_status` - `sprint_plan` - `sprint_move_goal` - `sprint_report` - `sprint_prioritize`