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 skills add michalparkola/tapestry-skills --skill ship-learn-nextgit clone --depth 1 https://github.com/michalparkola/tapestry-skillsWrote 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/skills/michalparkola/tapestry-skills/ship-learn-next)<a href="https://agentmods.dev/skills/michalparkola/tapestry-skills/ship-learn-next"><img src="https://agentmods.dev/badge/skills/michalparkola/tapestry-skills/ship-learn-next/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/skills/michalparkola/tapestry-skills/ship-learn-next"><img src="https://agentmods.dev/badge/skills/michalparkola/tapestry-skills/ship-learn-next.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 | $0.00056 | $0.02336 |
| Opus 5 | $0.00028 | $0.01168 |
| Sonnet 5 | $0.00011 | $0.00467 |
| Haiku 4.5 | $0.00006 | $0.00234 |
Grade A, and why
ship-learn-next 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 14d 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.
This is a copy
100% identical to ship-learn-next — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 327 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ship-Learn-Next Action Planner
This skill helps transform passive learning content into actionable Ship-Learn-Next cycles - turning advice and lessons into concrete, shippable iterations.
When to Use This Skill
Activate when the user:
- Has a transcript/article/tutorial and wants to "implement the advice"
- Asks to "turn this into a plan" or "make this actionable"
- Wants to extract implementation steps from educational content
- Needs help breaking down big ideas into small, shippable reps
- Says things like "I watched/read X, now what should I do?"
Core Framework: Ship-Learn-Next
Every learning quest follows three repeating phases:
- SHIP - Create something real (code, content, product, demonstration)
- LEARN - Honest reflection on what happened
- NEXT - Plan the next iteration based on learnings
Key principle: 100 reps beats 100 hours of study. Learning = doing better, not knowing more.
How This Skill Works
Step 1: Read the Content
Read the file the user provides (transcript, article, notes):
# User provides path to file
FILE_PATH="/path/to/content.txt"
Use the Read tool to analyze the content.
Step 2: Extract Core Lessons
Identify from the content:
- Main advice/lessons: What are the key takeaways?
- Actionable principles: What can actually be practiced?
- Skills being taught: What would someone learn by doing this?
- Examples/case studies: Real implementations mentioned
Do NOT:
- Summarize everything (focus on actionable parts)
- List theory without application
- Include "nice to know" vs "need to practice"
Step 3: Define the Quest
Help the user frame their learning goal:
Ask:
- "Based on this content, what do you want to achieve in 4-8 weeks?"
- "What would success look like? (Be specific)"
- "What's something concrete you could build/create/ship?"
Example good quest: "Ship 10 cold outreach messages and get 2 responses" Example bad quest: "Learn about sales" (too vague)
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.
- 14d ago First seen · 327 lines · 56 tokens per session scan A a040645a50e3
ship-learn-next is a skill published in the GitHub repository michalparkola/tapestry-skills (541 stars, last pushed 6mo ago), licensed MIT. It adds 56 tokens to every session and 2,336 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to ship-learn-next, differing in 4 lines, and is treated as a copy.
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