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Understand the pre-initialized Daytona volume filesystem. Use when operating inside a sandbox to know what directories exist, where to store state, how the memory DB works, and what guarantees hold across sessions.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
Delegate recursive work to child RLM sandboxes with budget management. Use when decomposing tasks into sub-queries, fanning out batched work, managing LLM call budgets, or building parent-child RLM hierarchies.
Diagnose fleet-rlm runtime failures, API contract drift, sandbox errors, and observability issues. Use when something is broken — Daytona connection failures, websocket mismatches, escalation not triggering, budget exhaustion, or missing traces.
Optimize fleet-rlm DSPy programs and RLM skill bundles using GEPA with MLflow tracking. Use when running optimization loops, designing feedback metrics, building training datasets, or comparing runs.
Hub skill for fleet-rlm: when to use dspy.RLM vs ReAct/CodeAct and which workflow skill to load next.
Design DSPy signatures and compose runtime modules for fleet-rlm tasks. Use when creating input/output field definitions, choosing between built-in signatures, selecting execution modes, or wiring custom modules.
Fetch and inspect JavaScript-heavy pages with Playwright in a Daytona browser-capable snapshot.
SOC 職業分類に基づく
| name | volume-bootstrap |
| description | Understand the pre-initialized Daytona volume filesystem. Use when operating inside a sandbox to know what directories exist, where to store state, how the memory DB works, and what guarantees hold across sessions. |
When you land inside a Daytona sandbox with a volume attached, the filesystem is already initialized. This skill explains what's there and how to use it.
When volume_name is set on the interpreter, the runtime automatically runs:
ensure_daytona_volume_layout() — creates all canonical directoriesinit_memory_db() — bootstraps SQLite schema at memories/core.dbseed_system_skills() — populates skills/system/ with bundled fleet-rlm skillsYou do NOT need to mkdir any standard directories. They exist.
MEMORY_ROOT/ ← /home/daytona/memory/
├── memories/
│ └── core.db ← SQLite persistent memory (auto-created)
├── knowledge/
│ ├── ingested/ ← Raw ingested files
│ └── summaries/ ← Generated summaries
├── skills/
│ ├── system/ ← Auto-seeded from fleet-rlm package
│ └── user/ ← User-added custom skills
├── sessions/<session_id>/
│ └── conversation.json ← Durable session manifest
├── logs/ ← Runtime logs
├── uploads/ ← Pre-ingestion file staging
├── memory/ ← (durable) key-value items
├── artifacts/ ← (durable) produced outputs
├── buffers/ ← (durable) named buffer lists
└── meta/ ← (durable) workspace metadata
MEMORY_ROOT is injected as a global in sandbox code. Use it instead of hardcoding paths.
# Write a fact (root agent only — depth-gated)
remember("project_language", "Python 3.12")
# Search memory (any agent depth can read)
results = recall("language")
# Returns up to 50 matches from core.db
# Accumulate items across execute() calls
add_buffer("findings", "First observation")
add_buffer("findings", "Second observation")
# Retrieve later in same session
items = get_buffer("findings") # ["First observation", "Second observation"]
# Load ingested document
content = load_document("knowledge/ingested/report.pdf")
# Search knowledge base
results = search_knowledge("deployment architecture")
# Load a bundled skill
skill_text = load_skill("rlm")
import json
from pathlib import Path
out = Path(MEMORY_ROOT) / "artifacts" / "analysis.json"
out.write_text(json.dumps({"status": "complete", "findings": [...]}))
| What | Persists across sessions? |
|---|---|
Everything under MEMORY_ROOT/ | Yes (same volume_name) |
memories/core.db entries | Yes |
Files in knowledge/, artifacts/, logs/ | Yes |
Session manifests in sessions/ | Yes |
| Workspace files (cloned repos, temp code) | No — transient |
Buffer contents (add_buffer) | No — session-scoped |
| Python variables and interpreter state | No — per-execute |
| Data type | Write to | Read back via |
|---|---|---|
| Factual memory | remember(key, value) | recall(query) |
| Generated artifacts | MEMORY_ROOT/artifacts/<name> | direct file read |
| Ingested documents | MEMORY_ROOT/knowledge/ingested/<name> | load_document(path) |
| Temporary staging | MEMORY_ROOT/uploads/ | process then move to knowledge/ |
| Structured logs | MEMORY_ROOT/logs/<name>.jsonl | direct file read |
| Session scratchpad | MEMORY_ROOT/sessions/<id>/scratch.json | direct file read |
VFS_CANONICAL_ROOTS.., %2e%2e, %2f, %5c) is rejected| Operation | Root agent (depth=0) | Child agent (depth>0) |
|---|---|---|
remember(key, value) | Allowed | Blocked (read-only) |
recall(query) | Allowed | Allowed |
| Direct file write to volume | Allowed | Allowed (if context isolation mode shares volume) |
add_buffer / get_buffer | Allowed | Allowed (own session scope) |