Skip to content
Back to skills

Context Loading

ASecurity

Load minimum necessary context into agent context windows. Prevents token bloat, reduces cost, and improves focus. Only load what the current task needs.

  • 65 stars
  • 0 votes
  • 0 copies
  • 1 view
  • Added May 26, 2026
ai-agentsgo

Works with

  • cursor

Security analysis

A100/100

Scanned May 27, 2026

npx -y skills add DevelopersGlobal/ai-agent-skills --skill context-loading --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Context Loading?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Context Loading
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/developersglobal-context-loading/badge)](https://www.skillsdirectory.com/skills/developersglobal-context-loading)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: context-loading
description: Load minimum necessary context into agent context windows. Prevents token bloat, reduces cost, and improves focus. Only load what the current task needs.
category: plan
applies-to: [claude, gemini, cursor, copilot, any]
version: 1.0.0
---

## Overview

More context is not better context. Irrelevant context dilutes attention, increases cost, and slows inference. This skill enforces disciplined context loading: only the files, docs, and history that the current task requires.

## When to Use

- Before starting any complex agent task
- When designing system prompts for production agents
- When context windows are filling up

## Process

### Step 1: Identify Required Context

1. List the files/docs the agent needs to read to complete THIS specific task.
2. For each item, ask: *"Can the agent complete the task without this?"* If yes, don't include it.
3. Prioritize: system prompt → task definition → directly relevant code → supporting references.

**Verify:** Every item in context is directly necessary for the current task.

### Step 2: Summarize, Don't Dump

4. Long conversation history → summarize to key decisions and current state.
5. Large files → extract only the relevant functions/sections.
6. Entire docs → extract only the relevant sections.
7. Previous agent output → extract only the conclusions and next steps.

**Verify:** No item in context exceeds what's needed from that source.

### Step 3: Set Context Budgets

8. Define token allocation for each context section:
   - System prompt: ≤ 2,000 tokens
   - Task definition: ≤ 500 tokens
   - Code context: ≤ 4,000 tokens
   - Conversation history (summarized): ≤ 1,000 tokens
9. Stay well within model context limits (leave 30% buffer for output).

**Verify:** Total prompt fits within 70% of model context limit.

### Step 4: Refresh Context for New Tasks

10. Don't carry over context from a completed task to a new task.
11. Start each distinct task with a fresh, minimal context.
12. Re-introduce only what the new task genuinely needs.

## Verification

- [ ] Context items limited to task-required items only
- [ ] Long content summarized before inclusion
- [ ] Token budget defined and respected
- [ ] Context window at ≤70% capacity

## References

- [rag-and-memory skill](../rag-and-memory/SKILL.md)
- [multi-agent-orchestration skill](../multi-agent-orchestration/SKILL.md)

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…