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Large File Interceptor

Community
ArchieIndian
large-file-interceptor

Detects oversized files that would blow the context window, generates structural exploration summaries, and stores compact references — preventing a single paste from consuming the entire budget.

Overview

PublisherArchieIndian
Repositoryopenclaw-superpowers
Skill namelarge-file-interceptor
Stars
74
Forks
14
Bundled files
3
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by ArchieIndian on GitHub. Read the source before you install it.

Installation

Install the Large File Interceptor AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/ArchieIndian/openclaw-superpowers/tree/main/skills/openclaw-native/large-file-interceptor
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/ArchieIndian/openclaw-superpowers.git /tmp/openclaw-superpowers
mkdir -p .claude/skills
cp -r /tmp/openclaw-superpowers/skills/openclaw-native/large-file-interceptor .claude/skills/large-file-interceptor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Large File Interceptor in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Large File Interceptor on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Large File Interceptor is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

bash
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 typeSummary includes
JSON/YAMLTop-level schema, key types, array lengths, nested depth
CSV/TSVColumn names, row count, sample values, data types per column
Python/JS/TSImports, class definitions, function signatures, export list
MarkdownHeading structure, word count per section, link count
Log filesTime range, error count, unique error patterns, frequency
Binary/OtherFile 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

bash
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

bash
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

bash
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

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Large File Interceptor AI skill do?

Detects oversized files that would blow the context window, generates structural exploration summaries, and stores compact references — preventing a single paste from consuming the entire budget.

Why use Large File Interceptor on TypingMind?

Because you install it once and use it with any model. Large File Interceptor is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Large File Interceptor in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ArchieIndian/openclaw-superpowers/tree/main/skills/openclaw-native/large-file-interceptor. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Large File Interceptor?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Large File Interceptor?

As many as you like. As long as a model supports skills, you can use Large File Interceptor with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Large File Interceptor AI skill free?

It is published on GitHub by ArchieIndian. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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