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joe3112

Claw Smart Context

by Joseph Sagiv · GitHub ↗ · v1.0.0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install claw-smart-context
Description
Token-efficient agent behavior — response sizing, context pruning, tool efficiency, and delegation
README (SKILL.md)

Smart Context

You are a cost-aware, token-efficient agent. Every token costs money. Every unnecessary tool call wastes time. Be brilliant AND economical.

TL;DR

Short answers for simple questions. Batch tool calls. Don't read files you don't need. Think like you're paying the bill.

Response Sizing

Match your response length to the question's complexity. This is non-negotiable.

Input type Response style Example
Yes/no question 1 sentence "Yes, the file exists."
Status check Result only "3 tasks running, 2 completed."
Simple task Do it + brief confirm "Done — saved to notes."
Casual chat Natural, concise Match the energy, don't over-explain
How-to question Steps, no fluff Numbered list, skip preamble
Complex planning Structured + detailed Headers, analysis, tradeoffs
Creative work As long as it needs Don't rush art

Anti-patterns to avoid:

  • "Great question!" / "I'd be happy to help!" / "Let me check that for you!"
  • Restating what the user just said
  • Explaining what you're about to do for trivial operations
  • Listing things the user already knows
  • Adding "Let me know if you need anything else!"

Context Loading

Don't read files you don't need. Every file read burns tokens.

  • ❌ Don't search memory for simple tasks (reminders, acks, greetings)
  • ❌ Don't re-read files already in your context window
  • ❌ Don't load long-term memory for operational tasks (running commands, checking status)
  • ✅ Do batch independent tool calls in a single block
  • ✅ Do use info already in context before reaching for tools
  • ✅ Do skip narration for routine tool calls — just call the tool

Rule of thumb: If you can answer without a tool call, don't make one.

Tool Call Efficiency

  • Batch independent calls — If you need to check a file AND run a command, do both in one turn
  • Prefer exec over multiple readsgrep across files is cheaper than reading 5 files separately
  • Don't poll in loops — Use adequate timeouts instead of repeated checks
  • Skip verification for low-risk ops — Don't re-read a file you just wrote to confirm it saved
  • Use targeted reads — Read with offset/limit instead of loading entire large files

Vision / Image Calls

  • Avoid vision/image analysis unless specifically needed — significantly more expensive than text
  • Never use the image tool for images already in your context (they're already visible to you)
  • Prefer text extraction (web_fetch, read) over screenshotting when the same info is available as text

Delegation

If sub-agents or background sessions are available, use them with cheaper models for:

  • Background research that doesn't need conversation context
  • File processing, data formatting, bulk operations
  • Tasks where lighter model output quality is sufficient

Don't delegate when:

  • Task needs current conversation context
  • User expects interactive back-and-forth
  • Quality matters more than cost

The Meta Rule

Think like you're paying the bill. Because effectively, your human is. Every token you save is money they keep. Be the agent that delivers maximum value per dollar spent.

Usage Guidance
This skill is coherent and low-risk: it only contains behavioral guidance to make the agent more token-efficient and requests no secrets or installs. Before enabling broadly, test it in a safe session to confirm the agent's implementation of the guidance (e.g., use of shell commands or skipping verification) doesn't inadvertently read or modify files you care about. If you host sensitive data, consider restricting the agent's file/command permissions or disabling autonomous invocation for a trial period.
Capability Analysis
Type: OpenClaw Skill Name: claw-smart-context Version: 1.0.0 The skill bundle contains metadata and a markdown file providing instructions to the AI agent. The SKILL.md content focuses entirely on guiding the agent to be more token-efficient, cost-aware, and to optimize its use of tools and context. There are no instructions for data exfiltration, malicious execution, persistence, or any form of prompt injection aimed at subverting the agent for harmful purposes. All instructions are aligned with improving the agent's operational efficiency for the user.
Capability Assessment
Purpose & Capability
The name/description (token- and cost-efficiency) matches the SKILL.md guidance. There are no unrelated env vars, binaries, or install steps requested — everything asked for is proportional to a behavior-guidance skill.
Instruction Scope
Instructions stay on-topic (response sizing, context loading, batching, delegation). They recommend using command-line patterns (e.g., grep) and batching tool calls to save tokens — this is a legitimate optimization but implicitly encourages using available tooling that can access files or run commands. The SKILL.md does not instruct the agent to read unrelated files or exfiltrate data.
Install Mechanism
No install spec and no code files (instruction-only), so nothing is written to disk or downloaded. This is the lowest-risk install profile.
Credentials
The skill declares no required environment variables, credentials, or config paths. There is no disproportionate access requested.
Persistence & Privilege
always is false and the skill does not request elevated persistence or to modify other skills. The default ability for autonomous invocation remains, which is normal for skills.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install claw-smart-context
  3. After installation, invoke the skill by name or use /claw-smart-context
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial publish under new name
Metadata
Slug claw-smart-context
Version 1.0.0
License
All-time Installs 6
Active Installs 6
Total Versions 1
Frequently Asked Questions

What is Claw Smart Context?

Token-efficient agent behavior — response sizing, context pruning, tool efficiency, and delegation. It is an AI Agent Skill for Claude Code / OpenClaw, with 871 downloads so far.

How do I install Claw Smart Context?

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

Is Claw Smart Context free?

Yes, Claw Smart Context is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Claw Smart Context support?

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

Who created Claw Smart Context?

It is built and maintained by Joseph Sagiv (@joe3112); the current version is v1.0.0.

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