filesystem-context
This skill should be used when the user asks to "offload context to files", "implement dynamic context discovery", "use filesystem for agent memory", "reduce context window bloat", or mentions file-based context management or just-in-time context loading.
SKILL.md
| Name | filesystem-context |
| Description | This skill should be used when the user asks to "offload context to files", "implement dynamic context discovery", "use filesystem for agent memory", "reduce context window bloat", or mentions file-based context management or just-in-time context loading. |
name: filesystem-context description: This skill should be used when the user asks to "offload context to files", "implement dynamic context discovery", "use filesystem for agent memory", "reduce context window bloat", or mentions file-based context management or just-in-time context loading.
Filesystem-Based Context Engineering
The filesystem provides a single interface through which agents can flexibly store, retrieve, and update effectively unlimited context. Files enable dynamic context discovery: agents pull relevant context on demand rather than carrying everything.
When to Activate
Activate this skill when:
- Tool outputs are bloating the context window
- Agents need to persist state across long trajectories
- Sub-agents must share information without direct message passing
- Tasks require more context than fits in the window
Core Patterns
Pattern 1: Filesystem as Scratch Pad
Write large tool outputs to files instead of returning directly to context.
def handle_tool_output(output: str, threshold: int = 2000) -> str:
if len(output) < threshold:
return output
file_path = f"scratch/{tool_name}_{timestamp}.txt"
write_file(file_path, output)
key_summary = extract_summary(output, max_tokens=200)
return f"[Output in {file_path}. Summary: {key_summary}]"
Pattern 2: Plan Persistence
Write plans to filesystem. Agent re-reads to remind itself of objectives.
# scratch/current_plan.yaml
objective: "Refactor authentication module"
status: in_progress
steps:
- id: 1
description: "Audit current auth endpoints"
status: completed
- id: 2
description: "Design new token validation"
status: in_progress
Pattern 3: Sub-Agent Communication via Filesystem
Sub-agents write findings directly. Coordinator reads files, bypassing message passing.
workspace/
agents/
research_agent/
findings.md
sources.jsonl
code_agent/
changes.md
test_results.txt
coordinator/
synthesis.md
Pattern 4: Dynamic Skill Loading
Store skills as files. Include only names/descriptions in static context.
Available skills (load with read_file when relevant):
- database-optimization: Query tuning and indexing
- api-design: REST/GraphQL best practices
Pattern 5: Terminal and Log Persistence
Sync terminal output to files. Agent greps for relevant sections.
grep -A 5 "error" terminals/1.txt
Pattern 6: Learning Through Self-Modification
Agents write learned information to their own instruction files.
def remember_preference(key: str, value: str):
prefs = load_yaml("agent/user_preferences.yaml")
prefs[key] = value
write_yaml("agent/user_preferences.yaml", prefs)
Filesystem Search Techniques
Combine these for comprehensive discovery:
ls/list_dir: Discover directory structureglob: Find files matching patterns (**/*.py)grep: Search file contents, returns matching linesread_filewith ranges: Read specific lines without loading entire files
This combination often outperforms semantic search for technical content.
File Organization
project/
scratch/ # Temporary working files
tool_outputs/ # Large tool results
plans/ # Active plans and checklists
memory/ # Persistent learned information
preferences.yaml
patterns.md
skills/ # Loadable skill definitions
agents/ # Sub-agent workspaces
When to Use
Use filesystem patterns when:
- Tool outputs exceed 2000 tokens
- Tasks span multiple conversation turns
- Multiple agents need to share state
- Skills/instructions exceed system prompt space
Avoid when:
- Tasks complete in single turns
- Context fits comfortably in window
- Latency is critical (file I/O adds overhead)
Guidelines
- Write large outputs to files; return summaries to context
- Store plans in structured files for re-reading
- Use sub-agent file workspaces instead of message chains
- Load skills dynamically rather than stuffing all into system prompt
- Combine grep/glob with semantic search for comprehensive discovery
- Implement cleanup for scratch files to prevent unbounded growth
Created: 2026-01-07 | Version: 1.0.0