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 skills/softaworks/agent-toolkit/ship-learn-nextnpx skills add softaworks/agent-toolkit --skill ship-learn-nextgit clone --depth 1 https://github.com/softaworks/agent-toolkitWhat 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 | $0.00056 | $0.02340 |
| Opus 5 | $0.00028 | $0.01170 |
| Sonnet 5 | $0.00011 | $0.00468 |
| 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 3d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- ship-learn-next — 100% identical, 4 lines differ
How it starts
The opening of the file, as written. The whole thing — 329 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 ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 329 lines · 56 tokens per session scan A 503b2265e8d9
ship-learn-next is a skill published in the GitHub repository softaworks/agent-toolkit (2,413 stars, last pushed 6mo ago), licensed MIT. It adds 56 tokens to every session and 2,340 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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