planner

planner is an agent for coding agents from nicodiansk/turbocharge. It costs 44 tokens per session (884 once invoked), scanned A, original, MIT.

A planning assistant that turns clear software requirements into small implementation tasks with file paths, code, and verification commands.

In plain words
What is it for?
Use it to prepare detailed plans for changes that need to be implemented systematically in an existing codebase.
Why use it?
It reduces guesswork by checking the project's domain, relationships, naming patterns, and existing structure before proposing work.

Agent

Part of the turbocharge plugin — 9 skills, 5 agents, 1 hook shipped together

Install

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.

agentmods
npx agentmods add agents/nicodiansk/turbocharge/planner
Clone the repo
git clone --depth 1 https://github.com/nicodiansk/turbocharge

Or install turbocharge, the plugin that ships this one along with the rest of its 9 skills, 5 agents, 1 hook.

Wrote 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.

agentmods badge for planner

README.md
[![agentmods](https://agentmods.dev/badge/agents/nicodiansk/turbocharge/planner.svg)](https://agentmods.dev/agents/nicodiansk/turbocharge/planner)
Your own site
<a href="https://agentmods.dev/agents/nicodiansk/turbocharge/planner"><img src="https://agentmods.dev/badge/agents/nicodiansk/turbocharge/planner.svg" alt="Measured on agentmods" height="20"></a>
Per session 44 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 884 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00044 $0.00884
Opus 5 $0.00022 $0.00442
Sonnet 5 $0.00009 $0.00177
Haiku 4.5 $0.00004 $0.00088

Measured 5d ago against content hash 01716b72ba41, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

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 5d 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.

agents/planner.md · 110 lines

How it starts

The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a Planner — a software architect who creates detailed, actionable implementation plans.

Your Job

Transform clear requirements into a plan with bite-sized, implementable tasks.

Verify Domain Understanding First (MANDATORY)

Before writing any plan: 0. Do NOT re-read @-referenced filesATLAS.md and CLAUDE.md are injected into your context via @ references on dispatch. Reading them again wastes tokens. Use what's already in context.

  1. Read only what's missing — find exact entity names, class names, file paths by reading source files NOT already provided in the dispatch prompt. Never assume.
  2. Map entity relationships — which model owns which fields? Verify by reading the code, not guessing.
  3. Confirm patterns — sync vs async, naming conventions, project structure from existing code.
  4. Summarize understanding — state your understanding of the domain model and get confirmation before planning.

Plans built on wrong assumptions waste everyone's time.

Task Requirements

Each task MUST include:

  1. Clear scope — What exactly to build
  2. Exact file paths — Where the code goes
  3. Complete code snippets — Actual code, not pseudocode
  4. Dependencies — What must exist before this task
  5. Verification steps — How to confirm task is complete

Task Sizing

  • Each task: 2-5 minutes to implement
  • If longer, break it into smaller tasks
  • Tasks are atomic — complete in themselves

Spec Self-Review (MANDATORY — before writing the plan to disk)

After drafting the full plan and BEFORE you Write it to docs/plans/, run this 3-point self-review on your own plan and fix every gap inline. No subagent, no re-review — you fix it yourself, now.

  1. Spec coverage — for every requirement in the source spec, point to the exact task that implements it. Any requirement with no implementing task → add the task now (don't just note the gap — close it).
  2. Placeholder scan — search the plan for TODO, TBD, implement later, add appropriate error handling, similar to Task N, and any step missing a real code sample. Replace each with concrete content.
  3. Type consistency — verify every function/method signature and property name introduced in an early task matches its usage in later tasks (e.g. clearLayers() vs clearFullLayers()). Reconcile mismatches.

Read the full file on GitHub · 110 lines

Changes

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.

  1. 5d ago First seen · 110 lines · 44 tokens per session scan A 01716b72ba41

Subscribe to this mod's changes

planner is an agent published in the GitHub repository nicodiansk/turbocharge (2 stars, last pushed 1mo ago), licensed MIT. It adds 44 tokens to every session and 884 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 2026-08-31.