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/agentic-engineeringnpx skills add drvoss/everything-copilot-cli --skill agentic-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 | $0.00040 | $0.02134 |
| Opus 5 | $0.00020 | $0.01067 |
| Sonnet 5 | $0.00008 | $0.00427 |
| Haiku 4.5 | $0.00004 | $0.00213 |
Grade A, and why
agentic-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 — 231 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agentic Engineering
Design tasks so AI agents can execute them reliably. This is not about using Copilot features — it is about architecting work so agents succeed on the first attempt, fail loudly when they can't, and hand off cleanly to the next agent.
Why This is Copilot-Exclusive
The patterns here are specific to Copilot CLI's agent execution model: task() dispatch, read_agent / write_agent lifecycle, SQL session state, and background agents with mode: "background". They don't map directly to interactive coding sessions in other tools.
When to Use
- Decomposing a large task before dispatching it to an agent or fleet
- Designing a multi-agent workflow where context must transfer between agents
- Debugging why an agent produced incorrect or incomplete output
- Establishing quality standards for a new agentic workflow
When NOT to Use
| Instead of agentic-engineering | Use |
|---|---|
| You already have tasks and just need to plan them | plan-mode-mastery |
| You need to assemble a specialist agent team | team-planner |
| You need autonomous execution guardrails | autopilot-patterns |
Core Principles
1. The 15-Minute Task Unit
Rule: Each agent dispatch should complete in roughly 15 minutes of human-equivalent focused work. In practice: 1–3 files changed, 1 clear outcome, no more than one decision required.
Why: Agents fail when context exceeds what fits in a single focused pass. Long tasks require the agent to hold too much state, make too many decisions, and produce outputs that are hard to verify.
Signs a task is too large:
- Description contains "and" more than twice
- Requires reading more than 5 files to complete
- Has more than one possible success state
- Cannot be verified by a single test or check
Signs a task is too small:
- It is just a file read or a lookup
- A single
editcall handles it entirely - No judgment is required
Decomposition pattern:
Large task: "Implement user authentication with JWT and refresh tokens"
↓ decompose
T-01: Add User schema + bcrypt password field (DB layer only)
T-02: Implement POST /auth/login endpoint (validate + sign JWT)
T-03: Implement POST /auth/refresh endpoint (validate refresh token)
T-04: Add auth middleware (extract + verify JWT on protected routes)
T-05: Integration tests for T-02, T-03, T-04
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 · 231 lines · 40 tokens per session scan A 55aa67284a8d
agentic-engineering is a skill published in the GitHub repository drvoss/everything-copilot-cli (45 stars, last pushed 5d ago), licensed MIT. It adds 40 tokens to every session and 2,134 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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