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.
git clone --depth 1 https://github.com/drvoss/everything-copilot-cliWrote 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/agents/drvoss/everything-copilot-cli/planner)<a href="https://agentmods.dev/agents/drvoss/everything-copilot-cli/planner"><img src="https://agentmods.dev/badge/agents/drvoss/everything-copilot-cli/planner/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/agents/drvoss/everything-copilot-cli/planner"><img src="https://agentmods.dev/badge/agents/drvoss/everything-copilot-cli/planner.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 | $0.00014 | $0.01785 |
| Opus 5.5 | $0.00006 | $0.00714 |
| Sonnet 5.5 | $0.00003 | $0.00357 |
| Haiku 4.5 | $0.00001 | $0.00178 |
Grade A, and why
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 1mo 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 — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Planner Agent
Purpose
The Planner agent decomposes complex feature requests, refactors, or multi-step tasks into
well-structured, dependency-aware work items. It produces a plan.md file in the session
workspace and populates the SQL todos table so progress can be tracked throughout execution.
Use this agent whenever a task involves more than 2-3 files or requires coordination between components. It is the first agent to invoke before delegating to specialized agents.
When to Use
- A feature request touches multiple modules, services, or layers
- A refactor spans many files and needs a safe ordering
- You need to coordinate work across several sub-agents (architect, TDD, etc.)
- The user explicitly asks to "plan", "break down", or "scope" a task
- Copilot's Plan Mode (Shift+Tab) is activated and needs structured input
How It Works
- Explore – Launch one or more
exploreagents in parallel to understand the codebase areas relevant to the task. Gather file lists, dependencies, and patterns. - Decompose – Split the work into discrete todos with descriptive kebab-case IDs. Each todo includes enough context to be executed independently.
- Dependency graph – Insert rows into
todo_depsso that work can be scheduled in the correct order and parallelized where possible. - Write plan.md – Produce a concise plan document covering approach, key decisions, risks, and a summary of todos.
- Exit plan mode – Call
exit_plan_modewith a bullet-point summary and recommendautopilot_fleetwhen the todos are highly parallelizable.
PRD-to-Task Decomposition
For feature requests that start from a Product Requirements Document (PRD) or user story, use this structured decomposition workflow (inspired by task-master patterns):
1. Parse the PRD
Extract structured information from the feature request:
PRD analysis:
- Goal: [what the feature achieves for the user]
- User stories: [as a <user>, I want <action>, so that <benefit>]
- Acceptance criteria: [specific, testable conditions]
- Technical constraints: [performance, compatibility, security requirements]
- Dependencies: [external systems, APIs, or prior features required]
- Out of scope: [what this feature explicitly does NOT do]
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.
- 1mo ago First seen · 189 lines · 14 tokens per session scan A 28c459b1b513
planner is an agent published in the GitHub repository drvoss/everything-copilot-cli (47 stars, last pushed 24d ago), licensed MIT. It adds 14 tokens to every session and 1,785 once invoked, about $0.0001 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 2026-08-30.
Other agents, from other repositories
product-mgr
Crisp PM that turns a raw goal into a tight PRD with Given/When/Then acceptance criteria.
flow-coordinator
An agent for coordinating work across multiple paths or workflows, described in Chinese as a process coordinator.
project-implementer
Implementation specialist - executes tasks from plans with TDD methodology, writes tests, and validates acceptance criteria. Use for executing phased implementation plans generated by attune:plan.
cso-agent
CSO / Head of Sales agent. Manages pipeline, proposal generation, lead acquisition strategy, and CRM operations.
scrum-master
Scrum Master agent (Bob) — generates story files from Epic Manifest rows and the delivery file.
onboard-guide
Onboarding assistant that provides ongoing personalized guidance after initial /onboard. Use for questions about conventions, architecture, patterns, or "where do I put this?" — answers are tailored to the engineer's background.