Initialize filesystem world by building catalog for prompt context
Scanned 6/6/2026
Install via CLI
openskills install bdambrosio/Cognitive_workbench---
name: init
type: python
description: "Initialize filesystem world by building catalog for prompt context"
---
# Filesystem Initialization Tool
Automatically executed during executor initialization to build a filesystem catalog that provides the agent with awareness of available files and directories in the sandbox.
## Purpose
This tool scans the filesystem sandbox (`scenarios/<world_name>/fs/`) and creates a structured catalog that is automatically included in planner prompts. This gives the agent initial awareness of:
- Directory structure
- Available files and their types
- Directory documentation (if present)
## Behavior
1. **Lightweight Scan**: Performs a limited-depth scan (max depth 2) with entry limits (30 per directory) to avoid performance issues
2. **Directory Documentation**: Reads `Skill.md`, `README.md`, or `DIRECTORY.md` files in directories and includes summaries
3. **Format Detection**: Identifies file types (text, json, binary, pdf) from extensions and samples
4. **Catalog Storage**: Stores the catalog in `world_state['_prompt_sections']['filesystem_catalog']` for generic retrieval by the executor
## Automatic Execution
- This tool is automatically executed during executor initialization if present
- Tool name must be `init` or `<world_name>-init` (e.g., `fs-init`)
- Runs after full tool catalog is loaded
- Executes via `execute_action_with_log()` so it's logged and published
## Output
The catalog is formatted as text and includes:
- Root directory path
- Directory tree structure (limited depth)
- File listings with type and size
- Directory documentation summaries (where available)
- Note about using fs-* tools for detailed exploration
## Limitations
- Limited depth scan (max 2 levels) to control token cost
- Entry limits (30 per directory) to avoid overwhelming prompts
- Performance warning logged if directories exceed 30 entries
## Integration
The catalog is retrieved generically by `executor.get_world_prompt_context()` and included in planner prompts without any world-specific code in the core planner.
No comments yet. Be the first to comment!
Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.
Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...
**Complete production-ready guide for Google Gemini embeddings API** This skill provides comprehensive coverage of the `gemini-embedding-001` model for generating text embeddings, including SDK usage, REST API patterns, batch processing, RAG integration with Cloudflare Vectorize, and advanced use cases like semantic search and document clustering. ---
Interview, source-challenge, verify, save, and ADR-gate fuzzy coding requests into Codex-ready implementation specs. Use when a feature, bugfix, refactor, migration, repo-wide change, or architecture task needs user-verified requirements, source-backed decisions, durable architecture decisions, acceptance criteria, validation commands, rollout notes, saved spec/ADR files, and a Codex execution prompt. Do not use when already fully specified or when the user wants direct implementation now.
Use when a repo needs CodeGraph plus ast-grep for Codex MCP setup, exploration, impact analysis, structural search, or safe refactor planning.