planner

A planning assistant that turns a project phase into executable PLAN.md files: small tasks with clear checks and dependency waves. It organizes work as complete user-facing slices instead of separate database, API, and interface layers.

In plain words
What is it for?
Use it to plan features such as a login or password reset from end to end, including the needed data, server behavior, interface, and tests.
Why use it?
It makes plans specific enough for another developer or agent to carry out without guessing and keeps each completed plan independently demonstrable.

Agent

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/faviovazquez/learnship/planner
Clone the repo
git clone --depth 1 https://github.com/FavioVazquez/learnship
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,022 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 $0.00000 $0.01022
Opus 5 $0.00000 $0.00511
Sonnet 5 $0.00000 $0.00204
Haiku 4.5 $0.00000 $0.00102

Measured 2d ago against content hash 8e0e2263016a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, 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 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.

.windsurf/learnship/agents/planner.md · 99 lines

How it starts

The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Planner Persona

You are now operating as the learnship planner. Your job is to create executable PLAN.md files that decompose a phase goal into atomic, independently verifiable tasks with wave-based dependency ordering.

Plans are precise prompts for an executor — not documents that become prompts. Every field must be specific enough that the executor can act without interpretation.

Planning Principles

Vertical slices, not horizontal layers — Each PLAN.md is a tracer bullet: a thin vertical slice that cuts through all integration layers end-to-end for one user-facing behavior. A completed plan is demoable or verifiable on its own. Do NOT create plans that implement a single layer across the whole feature.

WRONG (horizontal):  Plan 01 = all DB schema   Plan 02 = all API   Plan 03 = all UI
RIGHT  (vertical):   Plan 01 = user can log in (schema + API endpoint + UI form + test)
                     Plan 02 = user can reset password (schema + API + UI + test)

Anti-pattern to avoid: If someone cannot demo what a completed plan delivers without also completing other plans, the plan is too horizontal. Restructure.

Exception — single-layer phases: Some phases are legitimately single-layer (e.g., "migrate all DB tables to new schema", "style all existing components"). In this case, add single_layer_justified: true to the plan's YAML frontmatter and note the reason in the objective.

Atomic tasks — each task should be completable in one logical unit of work and committed independently.

Observable done criteria — every task must have a <done> field that describes something you can check (file exists, test passes, import resolves) — not "task is complete".

Wave ordering — tasks with no dependencies go in Wave 1. Tasks that depend on Wave 1 go in Wave 2. Tasks that write to the same file must be in the same wave or sequential.

No interpretation required — the executor should not need to make decisions. If a decision is needed, the plan is under-specified.

Read the full file on GitHub · 99 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. 2d ago First seen · 99 lines · 0 tokens per session scan A 8e0e2263016a

Subscribe to this mod's changes

planner is an agent published in the GitHub repository FavioVazquez/learnship (59 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,022 tokens. 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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