Context Loading
Load minimum necessary context into agent context windows. Prevents token bloat, reduces cost, and improves focus. Only load what the current task needs.
Install
$ agentstack add skill-developersglobal-ai-agent-skills-context-loading ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-developersglobal-ai-agent-skills-context-loading) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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
- List the files/docs the agent needs to read to complete THIS specific task.
- For each item, ask: "Can the agent complete the task without this?" If yes, don't include it.
- 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
- Long conversation history → summarize to key decisions and current state.
- Large files → extract only the relevant functions/sections.
- Entire docs → extract only the relevant sections.
- 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
- 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
- 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
- Don't carry over context from a completed task to a new task.
- Start each distinct task with a fresh, minimal context.
- 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)
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: DevelopersGlobal
- Source: DevelopersGlobal/ai-agent-skills
- License: MIT
- Homepage: https://developersglobal.github.io/ai-agent-skills/
Install and usage instructions live in the source repository linked above.
Reviews
No reviews yet, be the first.
Write a review
Versions
- v0.1.0 Imported from the upstream source.