aria_skills/skill_guide/SKILL.md
# skill_guide Self-documentation reader for Aria's skill system. ## Purpose Lets Aria **read any skill's SKILL.md** before calling its tools. This enables self-onboarding: when a new skill is added with a SKILL.md, Aria can read it on demand to understand usage, parameters, and examples. ## Layer **Layer 2 — Core** (available to all agents) ## Tools ### skill_guide__read Read a skill's documentation. | Parameter | Type | Required | Description | |----
npx skillsauth add najia-afk/aria_moltbot aria_skills/skill_guideInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Self-documentation reader for Aria's skill system.
Lets Aria read any skill's SKILL.md before calling its tools. This enables self-onboarding: when a new skill is added with a SKILL.md, Aria can read it on demand to understand usage, parameters, and examples.
Layer 2 — Core (available to all agents)
Read a skill's documentation.
| Parameter | Type | Required | Description |
|-------------|--------|----------|--------------------------------------------|
| skill_name | string | yes | Snake_case directory name (e.g. sandbox) |
When to use: Before calling tools from an unfamiliar skill, or when a tool call fails and you need to understand the expected parameters.
List all available skills with their layer, status, and description. No parameters required.
When to use: To discover what capabilities exist, or to find the
right skill name before calling skill_guide__read.
skill_guide__list to find which skill handles itskill_guide__read(skill_name="the_skill") to learn usagetools
# 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`