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/team-plannernpx skills add drvoss/everything-copilot-cli --skill team-plannergit 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 | $0.00042 | $0.03003 |
| Opus 5 | $0.00021 | $0.01502 |
| Sonnet 5 | $0.00008 | $0.00601 |
| Haiku 4.5 | $0.00004 | $0.00300 |
Grade A, and why
team-planner 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 — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Team Planner (Copilot-Native)
A Copilot CLI-native redesign of the “harness meta-skill” concept.
It does not assume Claude Code primitives like TeamCreate/TaskCreate exist. Instead, it uses Copilot CLI’s actual primitives:
tasktool (agent types:explore,task,general-purpose,code-review)/fleetfor parallel sub-agent execution- SQL session database for tracking (
sqltool) read_agent/write_agentfor monitoring and follow-ups
The lead planner acts as the conductor: it assigns ownership, coordinates sequencing, and decides when a second model should challenge or review another agent's output.
When to Use
- Task spans 3+ domains (e.g., security + performance + architecture)
- Work can be parallelized across independent specialists
- Need structured tracking of who does what and what’s done
NOT for: single-domain tasks, quick one-shot requests, tasks under ~30 minutes.
Pre-Flight Checklist
Before designing the team, verify all of the following:
- No duplicate agents: search
agents/andorchestration/skills/— avoid recreating a specialist that already exists - No slash commands: team-planner never creates slash command files in
.github/copilot/commands/— it only assembles work assignments - Parallelism confirmed: work can be split with no hard sequential dependencies between agents (if strong dependencies exist, use the Pipeline pattern instead)
- Scope justification: task spans 3+ distinct domains; single-domain tasks do not need a team
The 6 Phases (Copilot-native)
Phase 1: Analyze — Decompose the task
Copilot CLI reads the request, identifies the domains involved, and decomposes work into parallelizable units.
Outputs to produce in this phase:
- Domain list (e.g., security / performance / architecture / docs / testing)
- Rough effort estimate
- Risks and coordination points (shared files, ordering constraints)
Phase 2: Design the Team
Create a team roster in SQL.
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 · 302 lines · 42 tokens per session scan A 84f6122b4b1c
team-planner is a skill published in the GitHub repository drvoss/everything-copilot-cli (45 stars, last pushed 6d ago), licensed MIT. It adds 42 tokens to every session and 3,003 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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