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yuchen20

Context Crumb

by Yuchen Mao · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install context-crumb
Description
Use when an agent needs to read, inspect, summarize, or load large local prose-heavy files cheaply before sending them into LLM context. Best for Markdown do...
README (SKILL.md)

ContextCrumb

Purpose

Use ContextCrumb as a cheap first pass before reading large local text files into an LLM context window. It compresses by deleting lower-value words and punctuation while keeping the remaining text in original order.

ContextCrumb is for orientation and triage. Treat compressed output as shortened context, not authoritative source text.

When To Use

Use it before reading large natural-language files:

  • Documentation and Markdown
  • Notes and research dumps
  • Meeting transcripts
  • Issue threads and long discussions
  • Logs with lots of prose
  • Long comments or narrative text

When Not To Use

Do not rely on compressed output for exact syntax or exact wording:

  • Source code
  • Config files
  • Diffs and patches
  • JSON, YAML, TOML, XML, or schemas
  • Commands that may need to be copied exactly
  • Legal, compliance, policy, or contract text

For these files, read the raw source. If a file is too large, use ContextCrumb only to find likely relevant sections, then open the raw file around those sections before editing, quoting, or copying anything.

Default Workflow

If contextcrumb is already installed, use golden mode by default:

contextcrumb load \x3Cfile>

If the CLI is not installed and this is a one-off read, run it from PyPI:

uvx --from contextcrumb contextcrumb load \x3Cfile>

If repeated local use is expected, install it once:

python -m pip install contextcrumb

Then use:

contextcrumb load \x3Cfile>

Golden mode chooses an adaptive cutoff for each file and is the preferred default because it is conservative. If the output is still too large, use a fixed keep ratio only after checking the tradeoff:

contextcrumb load \x3Cfile> --target-keep-ratio 0.75
contextcrumb load \x3Cfile> --target-keep-ratio 0.5

Avoid aggressive ratios for first-pass reading unless the user explicitly asks for heavy compression.

Validation

Check compression savings without dumping the full output:

contextcrumb inspect \x3Cfile>

Check what was removed before trusting a compressed result:

contextcrumb diff \x3Cfile>

Use JSON only when another tool needs stats:

contextcrumb load \x3Cfile> --json

Read the text field as compressed context. Use stats.token_keep_ratio, stats.word_keep, and stats.model_windows to decide whether to retry with a different setting.

Practical Rules

  • Use contextcrumb load \x3Cfile> as the default.
  • Use uvx --from contextcrumb contextcrumb load \x3Cfile> for no-install one-off use.
  • Use installed CLI for repeated use.
  • Use inspect and diff before trusting compressed text for important work.
  • Never edit code, copy commands, or quote exact wording based only on compressed output.
Usage Guidance
Install only if you are comfortable using the ContextCrumb package on local documents. Use it for quick orientation on prose-heavy files, then check the original source before quoting, editing, copying commands, or making decisions involving sensitive or exact text.
Capability Assessment
Purpose & Capability
The stated purpose is to compress large prose-heavy local files before sending content into an LLM context window, and the instructions stay aligned with that purpose.
Instruction Scope
The skill clearly limits use to natural-language documents and warns users not to rely on compressed output for code, configs, commands, legal text, exact wording, or authoritative quoting.
Install Mechanism
The skill tells users to run an existing CLI or install/run the PyPI package via uvx or pip; this is disclosed and purpose-aligned, but it still means trusting that third-party package.
Credentials
The expected behavior is reading user-selected local files for compression; metadata also notes first-use public model-weight downloads and an optional local warm HTTP service, which are proportionate but worth understanding.
Persistence & Privilege
The artifact contains only a Markdown skill file and a small YAML prompt file, with no bundled executable scripts, persistence hooks, privilege escalation, credential handling, or automatic background behavior.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install context-crumb
  3. After installation, invoke the skill by name or use /context-crumb
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of ContextCrumb, a tool for fast, low-cost triage of large prose-heavy local files. - Compresses natural-language files by removing low-value words while preserving order. - Designed for context extraction from Markdown docs, notes, transcripts, issue threads, and narrative logs. - Output is for orientation and context only; not suitable for quoting or editing exact syntax. - Provides CLI commands for loading, inspecting, and diffing compressed files. - Includes guidance on optimal compression workflows and validation steps.
Metadata
Slug context-crumb
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Context Crumb?

Use when an agent needs to read, inspect, summarize, or load large local prose-heavy files cheaply before sending them into LLM context. Best for Markdown do... It is an AI Agent Skill for Claude Code / OpenClaw, with 77 downloads so far.

How do I install Context Crumb?

Run "/install context-crumb" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Context Crumb free?

Yes, Context Crumb is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Context Crumb support?

Context Crumb is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Context Crumb?

It is built and maintained by Yuchen Mao (@yuchen20); the current version is v1.0.0.

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