aria_skills/performance/SKILL.md
Log and query Aria's performance reviews and self-assessments.
npx skillsauth add najia-afk/aria_moltbot aria-performanceInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Log and query Aria's performance reviews, self-assessments, and improvement tracking.
exec python3 /app/skills/run_skill.py performance <function> '<json_args>'
Log a performance review entry.
exec python3 /app/skills/run_skill.py performance perf_log '{"period": "daily", "score": 85, "summary": "Completed 5 tasks, helped with code reviews", "strengths": ["fast responses", "code quality"], "improvements": ["context retention"]}'
Get performance history.
exec python3 /app/skills/run_skill.py performance perf_list '{"period": "daily", "limit": 10}'
Get performance trends and statistics.
exec python3 /app/skills/run_skill.py performance perf_stats '{"days": 30}'
GET /performance - List performance logsPOST /performance - Create performance entryperformance_log: | Column | Type | Description | |--------|------|-------------| | id | SERIAL | Primary key | | period | TEXT | Review period | | score | NUMERIC | Performance score | | summary | TEXT | Summary text | | strengths | JSONB | Strengths array | | improvements | JSONB | Improvements array | | metadata | JSONB | Additional data | | created_at | TIMESTAMP | Creation time |
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`