Agent Skill
2/7/2026

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.

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bthillerup
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npx skills add bthillerup/bens-garage-session-2

SKILL.md

Namefilesystem-context
DescriptionThis 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 structure
  • glob: Find files matching patterns (**/*.py)
  • grep: Search file contents, returns matching lines
  • read_file with 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

  1. Write large outputs to files; return summaries to context
  2. Store plans in structured files for re-reading
  3. Use sub-agent file workspaces instead of message chains
  4. Load skills dynamically rather than stuffing all into system prompt
  5. Combine grep/glob with semantic search for comprehensive discovery
  6. Implement cleanup for scratch files to prevent unbounded growth

Created: 2026-01-07 | Version: 1.0.0

Skills Info
Original Name:filesystem-contextAuthor:bthillerup