Agent Skills for Context Engineering is a collection of reusable instructions that teach AI agents how to manage their context, coordinate multi-agent systems, and evaluate behavior. Developers use it when building or debugging production agent systems, and the catalogue entries are skills, agents, instructions, and a plugin from this collection.
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 muratcankoylan/Agent-Skills-for-Context-Engineering --skill multi-agent-patternsgit clone --depth 1 https://github.com/muratcankoylan/Agent-Skills-for-Context-EngineeringWrote 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/muratcankoylan/agent-skills-for-context-engineering/multi-agent-patterns)<a href="https://agentmods.dev/skills/muratcankoylan/agent-skills-for-context-engineering/multi-agent-patterns"><img src="https://agentmods.dev/badge/skills/muratcankoylan/agent-skills-for-context-engineering/multi-agent-patterns.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Memory Poisoning · line 226 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
- medium Output Handling · line 251 Output from one security context is used in another without boundary enforcement. Cross-context output flow can leak sensitive information or escalate privileges across trust boundaries.Fix: Enforce strict context boundaries. Do not pass output from one security domain into another without explicit validation and redaction of sensitive content.
- medium Excessive Agency · line 228 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00042 | $0.03375 |
| Opus 5 | $0.00021 | $0.01688 |
| Sonnet 5 | $0.00008 | $0.00675 |
| Haiku 4.5 | $0.00004 | $0.00337 |
Grade A, and why
multi-agent-patterns 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 8d 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.
Copies of this mod
3 near-identical copies found in the catalogue:
- multi-agent-patterns — 100% identical, 0 lines differ
- multi-agent-patterns — 100% identical, 0 lines differ
- multi-agent-patterns — 98% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 268 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Multi-Agent Architecture Patterns
Multi-agent architectures distribute work across multiple language model instances, each with its own context window. When designed well, this distribution enables capabilities beyond single-agent limits. When designed poorly, it introduces coordination overhead that negates benefits. The critical insight is that sub-agents exist primarily to isolate context, not to anthropomorphize role division.
When to Activate
Activate this skill when:
- Single-agent context limits constrain task complexity
- Tasks decompose naturally into parallel subtasks
- Different subtasks require different tool sets or system prompts
- Building systems that must handle multiple domains simultaneously
- Scaling agent capabilities beyond single-context limits
- Designing production agent systems with multiple specialized components
Do not activate this skill for adjacent work owned by other skills:
- Deciding task-model fit, pipeline shape, or project-level cost before topology is known:
project-development. - Designing hosted sandboxes, warm pools, remote sessions, or background runtime infrastructure:
hosted-agents. - Sharing orchestrator state through KV-cache compaction in controlled runtimes:
latent-briefing. - Designing the tools each agent exposes:
tool-design.
Core Concepts
Use multi-agent patterns when a single agent's context window cannot hold all task-relevant information. Context isolation is the primary benefit — each agent operates in a clean context without accumulated noise from other subtasks, preventing the telephone game problem where information degrades through repeated summarization.
Choose among three dominant patterns based on coordination needs, not organizational metaphor:
- Supervisor/orchestrator — Use for centralized control when tasks have clear decomposition and human oversight matters. A single coordinator delegates to specialists and synthesizes results.
- Peer-to-peer/swarm — Use for flexible exploration when rigid planning is counterproductive. Any agent can transfer control to any other through explicit handoff mechanisms.
- Hierarchical — Use for large-scale projects with layered abstraction (strategy, planning, execution). Each layer operates at a different level of detail with its own context structure.
What ships with it
2 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.
- 8d ago First seen · 268 lines · 42 tokens per session scan A 786ff9345eb4
multi-agent-patterns is a skill published in the GitHub repository muratcankoylan/Agent-Skills-for-Context-Engineering (17,932 stars, last pushed 19d ago), licensed MIT. It adds 42 tokens to every session and 3,375 once invoked, about $0.0002 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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