Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/drvoss/everything-copilot-cli/context-engineeringnpx skills add drvoss/everything-copilot-cli --skill context-engineeringgit clone --depth 1 https://github.com/drvoss/everything-copilot-cliWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00024 | $0.01933 |
| Opus 5 | $0.00012 | $0.00966 |
| Sonnet 5 | $0.00005 | $0.00387 |
| Haiku 4.5 | $0.00002 | $0.00193 |
Grade A, and why
context-engineering scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 263 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context Engineering
When to Use
- Delegating a complex task to an AI agent
- An agent keeps repeating the wrong approach
- Agent quality drops as the context grows longer
- Designing a pipeline where multiple agents collaborate
Difference from
context-prime(Copilot-specific):
context-prime: loads live project context at session startcontext-engineering: structures the best possible information for a specific task
Prerequisites
- The delegated task has a clear goal and scope
- You know the relevant files or domain area
Workflow
1. Analyze signal vs. noise
Classify the information you plan to give the agent:
| Information type | Include? | Why |
|---|---|---|
| Directly relevant code files | ✅ Yes | The agent must edit or reason about them |
| Interface/type definitions | ✅ Yes | Essential for understanding contracts |
| Unrelated files | ❌ No | Waste tokens and reduce focus |
| Entire README | ❌ No (summarize instead) | Low information density for the size |
| Information the agent already has | ❌ No | Duplicate token cost |
2. Progressive Disclosure
Do not provide everything at once. Reveal only what each phase needs:
Phase 1: Task definition + interface contract
Phase 2: Implementation starts -> add relevant files
Phase 3: Testing -> add test patterns and references
3. Use a structured context template
Use this shape when instructing an agent:
## Task
[one clear objective]
## Given (what is already known)
- [file path]: [role]
- [interface contract]
## Constraints (what must not happen)
- [prohibited action]
- [files that must not be changed]
## Done When
- [ ] [specific, testable criterion]
4. Manage the context-window budget
Use context size intentionally. For exact model choice, see multi-model-strategy:
| Task complexity | Context size | Example |
|---|---|---|
| Short task (fast response first) | 2-3 files, clear goal | small bug fix, type addition |
| Medium task (balanced) | 5-10 files, interface contract | new API endpoint, component addition |
| Long task (deep reasoning first) | 10-20 files, module-level context | architecture refactor, complex bug |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 263 lines · 24 tokens per session scan A c250c758e5a9
context-engineering is a skill published in the GitHub repository drvoss/everything-copilot-cli (45 stars, last pushed 5d ago), licensed MIT. It adds 24 tokens to every session and 1,933 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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