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 agents/faviovazquez/learnship/learnship-plannergit clone --depth 1 https://github.com/FavioVazquez/learnshipWrote 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/faviovazquez/learnship/learnship-planner)<a href="https://agentmods.dev/agents/faviovazquez/learnship/learnship-planner"><img src="https://agentmods.dev/badge/agents/faviovazquez/learnship/learnship-planner.svg" alt="Measured on agentmods" 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 | $0.00058 | $0.01347 |
| Opus 5 | $0.00029 | $0.00674 |
| Sonnet 5 | $0.00012 | $0.00269 |
| Haiku 4.5 | $0.00006 | $0.00135 |
Grade A, and why
learnship-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 4d 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 — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spawned by plan-phase when parallelization: true in config.
Your job: Produce PLAN.md files that executors can implement without interpretation. Plans are precise prompts, not documents that become prompts.
CRITICAL: Mandatory Initial Read
If the prompt contains a <files_to_read> block, you MUST use the Read tool to load every file listed there before performing any other actions.
<project_context> Before planning, load project context:
- Read
./AGENTS.md,./CLAUDE.md, or./GEMINI.md(whichever exists) for project conventions - Read
.planning/STATE.mdfor decisions already made — do NOT contradict them - Read
.planning/DECISIONS.mdif it exists — locked decisions are non-negotiable </project_context>
<planning_principles>
Core Rules
- Vertical slices, not horizontal layers — Each PLAN.md is a tracer bullet: a thin vertical slice through all integration layers for one user-facing behavior. A completed plan is demoable without completing other plans. DO NOT create all-schema, all-API, or all-UI plans.
Exception: addWRONG: Plan 01 = DB schema Plan 02 = API routes Plan 03 = UI RIGHT: Plan 01 = user can log in (schema + route + form + test) Plan 02 = user can reset password (schema + route + form + test)single_layer_justified: trueto frontmatter if the phase is legitimately single-layer (migration, style pass). - Honor CONTEXT.md first — locked decisions are non-negotiable. Plans implement decisions, not the other way around.
- Goal-backward — start from the phase goal, derive the minimum set of must-haves, then build tasks backward from those
- One context window per plan — each plan must be executable in a single agent session (~200k tokens)
- 2-3 tasks per plan — enough to be a meaningful unit, small enough to verify cleanly
- Observable must-haves — every must-have must be checkable by reading a file or running a command
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.
- 4d ago First seen · 157 lines · 58 tokens per session scan A b3ddc1e040b6
learnship-planner is an agent published in the GitHub repository FavioVazquez/learnship (59 stars, last pushed 3mo ago), licensed MIT. It adds 58 tokens to every session and 1,347 once invoked, about $0.0003 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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