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 HsuanYuLee/polaris --skill learninggit clone --depth 1 https://github.com/HsuanYuLee/polarisWrote 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/hsuanyulee/polaris/learning)<a href="https://agentmods.dev/skills/hsuanyulee/polaris/learning"><img src="https://agentmods.dev/badge/skills/hsuanyulee/polaris/learning/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/hsuanyulee/polaris/learning"><img src="https://agentmods.dev/badge/skills/hsuanyulee/polaris/learning.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 | $0.00180 | $0.01872 |
| Opus 5.5 | $0.00072 | $0.00749 |
| Sonnet 5.5 | $0.00036 | $0.00374 |
| Haiku 4.5 | $0.00018 | $0.00187 |
Grade A, and why
learning 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 11d 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
learning
learning 把外部資料、文章 queue、PR review lessons、daily scanner setup
轉成可落地的 workspace knowledge。SKILL.md 只保留 mode routing、邊界與
必讀 reference；mode 細節延後載入。
Mandatory Contracts
- 任何 sub-agent dispatch 前，先說出它要回傳什麼（Completion Envelope），並要求它把
完整分析寫進一個檔案（
/tmp/polaris-agent-{timestamp}.md），主 session 只收摘要。 envelope 的形狀由派工的那一份 flow 自己定義——PR / Batch 在learning-pr-batch-flow.md，queue 在learning-queue-flow.md。 - 任何 Slack / JIRA / GitHub / Confluence 或其他 external write 前，遵守
scripts/validate-language-policy.sh或 external write gate。 - 任何 specs Markdown 產出或匯入，遵守
starlight-authoring-contract.md。 - Learning 可以 seed / import research evidence，但不得自動 invoke
refinement， 也不得替任何已凍結的 assertion 改寫成功的定義。 - 寫入 handbook、backlog、learnings、README acknowledgement、RemoteTrigger 或 specs artifact 後，最後必跑 Post-Task Reflection。
Mode Detection
依使用者輸入選 mode；只讀該 mode 的 reference。
| Signal | Mode | Reference |
|---|---|---|
PR number、PR URL、PR + 學習/learn、某人的 PR、時間範圍 + PR |
PR mode | learning-pr-batch-flow.md |
掃 review、batch learn、批次學習、掃歷史 PR、補齊 review lessons |
Batch mode | learning-pr-batch-flow.md |
| 外部 URL、GitHub repo、文章、local research file、使用者貼的研究題材 | External mode | learning-external-flow.md |
每日學習、今天有什麼可以學的、有新文章嗎、讀文章、daily learning、queue、bare 學習 without URL/PR context |
Queue mode | learning-queue-flow.md |
設定學習、learning setup、更新學習主題、scanner 設定、learning scanner |
Setup mode | learning-setup-flow.md |
| 模糊輸入 | Ask one concise clarification | N/A |
首次使用但 daily scanner 尚未設定時，提示使用者可用 設定學習 或
learning setup 啟用每日文章推薦。
External Mode Contract
讀 learning-external-flow.md。外部學習必須先判斷 target：
framework：Polaris / 框架 / AI agent pattern / skill / rule / mechanism。project:{name}：使用者指定產品 repo 或目前工作脈絡可明確推導。- ambiguous：詢問「這個學習要用在 Polaris 框架，還是特定產品 repo？」
GitHub repo 若包含 .claude/skills/、SKILL.md 或 skills/，探索前先跑
.claude/skills/learning/scripts/skill-sanitizer.py pre-scan；HIGH/CRITICAL 風險需讓使用者確認是否繼續。
What ships with it
24 files 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.
- references/learning-external-flow.md 8.9 KB
- references/learning-pr-batch-flow.md 4.9 KB
- references/learning-queue-flow.md 3.2 KB
- references/learning-setup-flow.md 5.7 KB
- references/review-lesson-extraction.md 6.8 KB
- references/starlight-authoring-contract.md 7.7 KB
- scripts/lib/main-checkout.sh 1.9 KB runs code
- scripts/lib/specs-root.sh 4.2 KB runs code
- scripts/lib/validate_dp_metadata_1.py 10 KB runs code
- scripts/lib/validate_language_policy_1.py 11 KB runs code
- scripts/lib/validate_learning_seed_contract_1.py 6.9 KB runs code
- scripts/lib/validate_specs_collection_shape_1.py 2.6 KB runs code
- scripts/lib/validate_starlight_authoring_1.py 8.3 KB runs code
- scripts/lib/workspace-config-root.sh 2.6 KB runs code
- scripts/polaris-embed-setup.sh 917 B runs code
- scripts/polaris-embed.py 7.5 KB runs code
- scripts/polaris-learnings.sh 9.8 KB runs code
- scripts/skill-sanitizer.py 23 KB runs code
- scripts/sync-spec-sidebar-metadata.sh 9.9 KB runs code
- scripts/validate-dp-metadata.sh 769 B runs code
- scripts/validate-language-policy.sh 9.2 KB runs code
- scripts/validate-learning-seed-contract.sh 281 B runs code
- scripts/validate-specs-collection-shape.sh 4.1 KB runs code
- scripts/validate-starlight-authoring.sh 639 B runs code
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.
- 11d ago Changed · +1 lines bf4efae007b0
- 1mo ago First seen · 125 lines · 180 tokens per session scan A ff6bd5376e89
learning is a skill published in the GitHub repository HsuanYuLee/polaris (5 stars, last pushed 2d ago), licensed MIT. It adds 180 tokens to every session and 1,872 once invoked, about $0.0007 per session on Opus 5.5. 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 2026-08-31.
Other skills, from other repositories
understand-explain
Use when you need a deep-dive explanation of a specific file, function, or module in the codebase.
baoyu-comic
A tool for creating original educational comics that explain knowledge or ideas through multiple illustrated panels. It supports different art styles and tones and can create several comics in one batch.
skill-creation-walkthrough
Step-by-step guide for creating your own Claude Skills, from deciding whether a skill is the right tool to writing the SKILL.md file, structuring reference material, and making it trigger reliably. Use when you want to package a workflow, framework, or repeated task into a reusable Skill, when an existing skill is not…
learning-and-development
Builds capability — skills gaps, career frameworks, training that transfers to the job, and internal mobility. Use this to design a career ladder, close a capability gap, decide whether to build or hire a skill, structure onboarding into a role, or work out why training keeps failing to change anything.
render-whiteboard-explainer
Assemble a whiteboard explainer video ad from a beats file — a narrator explains one idea while a real whiteboard fills up in black marker, with a hand-lettered title, bulleted rows down the left, a drawing filling the right, and a payoff that letters the closing line and rings the claim. The board is a PHOTOGRAPH and…
elixir-idioms
OTP/BEAM patterns and Elixir idioms — GenServer, Supervisor, Task, Registry, pattern matching, with chains, pipes. Use when designing processes or debugging BEAM issues.