Context Engineering Template is a repository of instructions, examples, workflows, and validation practices that give AI coding assistants the information they need to complete software tasks. It is for developers working with Claude Code or other coding assistants, and the catalogue entries package parts of its workflow as commands, agents, instructions, and a skill.
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 coleam00/context-engineering-intro --skill build-with-agent-teamgit clone --depth 1 https://github.com/coleam00/context-engineering-introWrote 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/coleam00/context-engineering-intro/build-with-agent-team)<a href="https://agentmods.dev/skills/coleam00/context-engineering-intro/build-with-agent-team"><img src="https://agentmods.dev/badge/skills/coleam00/context-engineering-intro/build-with-agent-team/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/coleam00/context-engineering-intro/build-with-agent-team"><img src="https://agentmods.dev/badge/skills/coleam00/context-engineering-intro/build-with-agent-team.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00000 | $0.02983 |
| Opus 5 | $0.00000 | $0.01491 |
| Sonnet 5 | $0.00000 | $0.00597 |
| Haiku 4.5 | $0.00000 | $0.00298 |
Grade A, and why
build-with-agent-team scanned grade A with 1 finding 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 10d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- "Backend: what exact curl commands test each endpoint?" How it starts
The opening of the file, as written. The whole thing — 358 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Build with Agent Team
You are coordinating a build using Claude Code Agent Teams. Read the plan document, determine the right team structure, spawn teammates, and orchestrate the build.
Arguments
- Plan path:
$ARGUMENTS[0]- Path to a markdown file describing what to build - Team size:
$ARGUMENTS[1]- Number of agents (optional)
Step 1: Read the Plan
Read the plan document at $ARGUMENTS[0]. Understand:
- What are we building?
- What are the major components/layers?
- What technologies are involved?
- What are the dependencies between components?
Step 2: Determine Team Structure
If team size is specified ($ARGUMENTS[1]), use that number of agents.
If NOT specified, analyze the plan and determine the optimal team size based on:
- Number of independent components (frontend, backend, database, infra, etc.)
- Technology boundaries (different languages/frameworks = different agents)
- Parallelization potential (what can be built simultaneously?)
Guidelines:
- 2 agents: Simple projects with clear frontend/backend split
- 3 agents: Full-stack apps (frontend, backend, database/infra)
- 4 agents: Complex systems with additional concerns (testing, DevOps, docs)
- 5+ agents: Large systems with many independent modules
For each agent, define:
- Name: Short, descriptive (e.g., "frontend", "backend", "database")
- Ownership: What files/directories they own exclusively
- Does NOT touch: What's off-limits (prevents conflicts)
- Key responsibilities: What they're building
Step 3: Set Up Agent Team
Enable tmux split panes so each agent is visible:
teammateMode: "tmux"
Step 4: Define Contracts
Before spawning agents, the lead reads the plan and defines the integration contracts between layers. This focused upfront work is what enables all agents to spawn in parallel without diverging on interfaces. Agents that build in parallel will diverge on endpoint URLs, response shapes, trailing slashes, and data storage semantics unless they start with agreed-upon contracts.
What ships with it
3 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.
- 10d ago First seen · 358 lines · 0 tokens per session scan A 3d1a590a7a90
build-with-agent-team is a skill published in the GitHub repository coleam00/context-engineering-intro (13,825 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,983 tokens. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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