large-file-interceptor

SKILL.md

Large File Interceptor

What it does

A single large file paste can consume 60–80% of the context window, leaving no room for actual work. Large File Interceptor detects oversized files, generates a structural summary (schema, columns, imports, key definitions), stores the original externally, and replaces it with a compact reference card.

Inspired by lossless-claw's large file interception layer, which automatically extracts files exceeding 25k tokens.

When to invoke

  • Before processing any file the agent reads or receives — check size first
  • When context budget is running low and large files may be the cause
  • After a paste or file read — retroactively scan for oversized content
  • Periodically to audit what's consuming the most context budget

How to use

python3 intercept.py --scan <path>                # Scan a file or directory
python3 intercept.py --scan <path> --threshold 10000  # Custom token threshold
python3 intercept.py --summarize <file>           # Generate structural summary for a file
python3 intercept.py --list                       # List all intercepted files
python3 intercept.py --restore <ref-id>           # Retrieve original file content
python3 intercept.py --audit                      # Show context budget impact
python3 intercept.py --status                     # Last scan summary
python3 intercept.py --format json                # Machine-readable output

Structural exploration summaries

The interceptor generates different summaries based on file type:

File type Summary includes
JSON/YAML Top-level schema, key types, array lengths, nested depth
CSV/TSV Column names, row count, sample values, data types per column
Python/JS/TS Imports, class definitions, function signatures, export list
Markdown Heading structure, word count per section, link count
Log files Time range, error count, unique error patterns, frequency
Binary/Other File size, MIME type, magic bytes

Reference card format

When a file is intercepted, the original is stored in ~/.openclaw/lcm-files/ and replaced with:

[FILE REFERENCE: ref-001]
Original: /path/to/large-file.json
Size: 145,230 bytes (~36,307 tokens)
Type: JSON — API response payload

Structure:
  - Root: object with 3 keys
  - "data": array of 1,247 objects
  - "metadata": object (pagination, timestamps)
  - "errors": empty array

Key fields in data[]: id, name, email, created_at, status
Sample: {"id": 1, "name": "...", "status": "active"}

To retrieve full content: python3 intercept.py --restore ref-001

Procedure

Step 1 — Scan before processing

python3 intercept.py --scan /path/to/file.json

If the file exceeds the token threshold (default: 25,000 tokens), it generates a structural summary and stores a reference.

Step 2 — Audit context impact

python3 intercept.py --audit

Shows all files in the current workspace ranked by token impact, with recommendations for which to intercept.

Step 3 — Restore when needed

python3 intercept.py --restore ref-001

Retrieves the original file content from storage for detailed inspection.

State

Intercepted file registry and reference cards stored in ~/.openclaw/skill-state/large-file-interceptor/state.yaml. Original files stored in ~/.openclaw/lcm-files/.

Fields: last_scan_at, intercepted_files, total_tokens_saved, scan_history.

Notes

  • Never deletes or modifies original files — intercept creates a copy + reference
  • Token threshold is configurable (default: 25,000 ~= 100KB of text)
  • Reference cards are typically 200–400 tokens vs. 25,000+ for the original
  • Supports recursive directory scanning with --scan /path/to/dir
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