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 skills add BuilderCed/agent-skills --skill context-engineeringgit clone --depth 1 https://github.com/BuilderCed/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/builderced/agent-skills/context-engineering)<a href="https://agentmods.dev/skills/builderced/agent-skills/context-engineering"><img src="https://agentmods.dev/badge/skills/builderced/agent-skills/context-engineering/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/builderced/agent-skills/context-engineering"><img src="https://agentmods.dev/badge/skills/builderced/agent-skills/context-engineering.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00028 | $0.00915 |
| Opus 5.5 | $0.00011 | $0.00366 |
| Sonnet 5.5 | $0.00006 | $0.00183 |
| Haiku 4.5 | $0.00003 | $0.00092 |
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 1mo 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context Engineering
Based on ETH Zurich research: overly detailed instructions reduce task success by 3%, increase token cost by 20%, and add 2-4 reasoning steps.
When to Use
- Writing SKILL.md, AGENTS.md, or system prompts
- Debugging poor agent performance
- Optimizing token costs
- Designing multi-agent workflows
- Reducing context window pressure
Context Hierarchy (5 Levels)
Most persistent → most transient:
| Level | Content | Persistence | Example |
|---|---|---|---|
| 1. Rules | Project-wide standards | Always loaded | CLAUDE.md, AGENTS.md |
| 2. Spec | Feature/session scope | Per feature | PRD, architecture docs |
| 3. Source | Per task | Per task | Relevant source files |
| 4. Errors | Per iteration | Per attempt | Test failures, stack traces |
| 5. History | Accumulates | Session | Conversation history |
Principle: Levels 1-2 are curated (high leverage). Levels 3-5 are per-call (keep minimal).
What to Include
Include ONLY what the agent cannot discover independently:
- Non-obvious conventions ("we use snake_case for DB columns")
- Project-specific constraints ("never modify the auth module")
- Architectural decisions not in code ("we chose Drizzle over Prisma because...")
- External dependencies not discoverable ("deploy via internal CI, not GitHub Actions")
What NOT to Include
The agent can discover these itself — including them wastes tokens:
- Tech stack (visible in package.json / requirements.txt)
- File structure (visible via ls / find)
- Key files (visible via search)
- Build commands (visible in scripts / Makefile)
- Standard patterns (the model already knows React, Express, etc.)
Sizing Guidelines
| Context Type | Max Size | Rationale |
|---|---|---|
| AGENTS.md | 500-1000 tokens | ETH Zurich: more = worse |
| SKILL.md (core) | 1000-2500 tokens | Balance detail vs overhead |
| references/ per skill | 500-1000 tokens | Support data, not duplicate |
| System prompt total | < 5K tokens | Beyond this: diminishing returns |
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.
- 1mo ago First seen · 99 lines · 28 tokens per session scan A 945856399f0e
context-engineering is a skill published in the GitHub repository BuilderCed/agent-skills (2 stars, last pushed 6mo ago), licensed MIT. It adds 28 tokens to every session and 915 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-31.
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