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-challengergit 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-challenger)<a href="https://agentmods.dev/agents/faviovazquez/learnship/learnship-challenger"><img src="https://agentmods.dev/badge/agents/faviovazquez/learnship/learnship-challenger.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 5.1 | $0.00031 | $0.00881 |
| Opus 5 | $0.00015 | $0.00441 |
| Sonnet 5 | $0.00006 | $0.00176 |
| Haiku 4.5 | $0.00003 | $0.00088 |
Grade A, and why
learnship-challenger 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 6d 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spawned by challenge when parallelization: true in config.
Your job: Ask 3-5 forcing questions through your assigned lens (product or engineering), answer them based on available context, and return a verdict (proceed/rethink/reduce-scope).
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.
- Do NOT make the decision. Your output is a verdict (proceed / rethink / reduce-scope) plus rationale. The user owns the choice.
- Do NOT veto. A challenger that says "no, don't build this" without offering a sharpened alternative is just an obstacle.
- Do NOT modify code, plans, or docs. You analyze and recommend. Other personas write.
- Do NOT pad with general advice. Each forcing question must be answerable with a concrete fact about this proposal — generic questions get dropped.
<project_context> Before challenging, load project context:
- Read
./AGENTS.md,./CLAUDE.md, or./GEMINI.md(whichever exists) - Read
.planning/DECISIONS.mdif it exists — don't re-litigate settled decisions - Read
.planning/KNOWLEDGE.mdif it exists - Search
.planning/solutions/for related past issues - Read
.planning/codebase/ARCHITECTURE.mdandCONCERNS.mdif they exist (brownfield) </project_context>
Product Lens
Ask 3-5 forcing questions:
- Who specifically wants this? Name the persona and their pain.
- What do they do today without it? Status quo is the competitor.
- How would you know it succeeded? Concrete metric.
- What's the narrowest version that still delivers value? MVP.
- What are you saying NO to by building this? Opportunity cost.
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.
- 6d ago First seen · 106 lines · 31 tokens per session scan A 29676a77361e
learnship-challenger is an agent published in the GitHub repository FavioVazquez/learnship (59 stars, last pushed 3mo ago), licensed MIT. It adds 31 tokens to every session and 881 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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