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 abossenbroek/abossenbroek-claude-plugins --skill context-engineeringgit clone --depth 1 https://github.com/abossenbroek/abossenbroek-claude-pluginsWrote 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/abossenbroek/abossenbroek-claude-plugins/context-engineering)<a href="https://agentmods.dev/skills/abossenbroek/abossenbroek-claude-plugins/context-engineering"><img src="https://agentmods.dev/badge/skills/abossenbroek/abossenbroek-claude-plugins/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/abossenbroek/abossenbroek-claude-plugins/context-engineering"><img src="https://agentmods.dev/badge/skills/abossenbroek/abossenbroek-claude-plugins/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 | $0.00064 | $0.00954 |
| Opus 5.5 | $0.00026 | $0.00382 |
| Sonnet 5.5 | $0.00013 | $0.00191 |
| Haiku 4.5 | $0.00006 | $0.00095 |
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 2mo 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context Engineering
Overview
State-of-the-art patterns for managing context in LLM agent systems. These patterns enable complex multi-agent workflows while minimizing token overhead through strategic context engineering.
The Four Laws of Context Management
| Law | Principle | Token Impact |
|---|---|---|
| 1. Selective Projection | Pass only fields each agent needs | -30-50% |
| 2. Tiered Fidelity | Define explicit context tiers per role | -40-60% |
| 3. Reference vs Embedding | Use references for large data | -50-80% |
| 4. Lazy Loading | Load data on-demand, not upfront | -30-50% |
For detailed explanations and examples, see references/four-laws.md.
Context Tiers
| Tier | Description | Use Case | Typical Size |
|---|---|---|---|
| FULL | Complete data | Initial analysis | 5-20K tokens |
| SELECTIVE | Relevant subset | Domain workers | 1-5K tokens |
| FILTERED | Criteria-matched | Validators | 500-2K tokens |
| MINIMAL | Mode + counts | Routing | 100-500 tokens |
| METADATA | Stats only | Synthesis | 50-200 tokens |
For tier selection guidance, see references/context-tiers.md.
Quick Reference: Input Section Pattern
Before (Anti-pattern)
## Input
You receive:
- snapshot: Full context snapshot
- all_findings: Complete list
- full_config: Everything
After (SOTA Pattern)
## Input
You receive (SELECTIVE context):
- analysis_summary: Key findings only
- relevant_files: Files for this focus area
- mode: Analysis depth setting
**NOT provided** (context isolation):
- Full plugin contents
- Unrelated analysis results
- Other agents' intermediate work
Anti-Patterns to Avoid
| Anti-Pattern | Problem | Fix |
|---|---|---|
| Snapshot Broadcasting | Same data to every agent | Tier by role |
| Defensive Inclusion | "Maybe they need this" | Document NOT PASSED |
| Grounding Everything | Validating low-priority | Severity batching |
| Large Embeddings | Full arrays when counts suffice | Reference pattern |
| Repeated Context | Same data multiple times in chain | Pass once, reference later |
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 135 lines · 64 tokens per session scan A 7e2559ece8c0
Context Engineering is a skill published in the GitHub repository abossenbroek/abossenbroek-claude-plugins (2 stars, last pushed 6mo ago), licensed BSD-3-Clause. It adds 64 tokens to every session and 954 once invoked, about $0.0003 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.
Context Engineering compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| Context Engineeringabossenbroek/abossenbroek-claude-plugins | Skill | 2 | 6mo ago | BSD-3-Clause | A | 64 | Claude Code |
| knowledge-ingestopenclaw/openclaw | Skill | 394k | today | MIT | A | 80 | Claude Code, Codex |
| mem0-oss-to-platformmem0ai/mem0 | Skill | 69k | yesterday | Apache-2.0 | A | 217 | Claude Code, Codex |
| forgetasgeirtj/system_prompts_leaks | Skill | 71k | yesterday | CC0-1.0 | A | 0 | Claude Code, Codex |
| Cortexdanielmiessler/LifeOS | Skill | 20k | 2d ago | MIT | A | 184 | Claude Code |
| ha-data-storesshiwenwen/hope-agent | Skill | 1.9k | today | MIT | A | 115 | Claude Code, Codex |
| memoryopensquilla/opensquilla | Skill | 7.1k | 7d ago | Apache-2.0 | A | 44 | Claude Code, Codex |