AgentStack
Browse Sign in
Browse Why AgentStack Sell Docs
Sign in
SKILL verified MIT Self-run

Lessons

skill-chewbaccaroars-pathfinder-skills-lessons · by ChewbaccaRoars

A Claude skill from ChewbaccaRoars/pathfinder-skills.

No reviews yet
0 installs
28 views
0.0% view→install

Install

$ agentstack add skill-chewbaccaroars-pathfinder-skills-lessons

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

Verified badge

Passed review? Show it. Paste this badge into your README, it links to the public security report.

AgentStack Verified badge Links to your public security report.
[![AgentStack Verified](https://agentstack.voostack.com/badges/verified.svg)](https://agentstack.voostack.com/security/report/skill-chewbaccaroars-pathfinder-skills-lessons)

Reliability & compatibility

Security review passed
0 installs to date
no reviews yet
6mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.

How agent discovery & health will work →
Are you the author of Lessons? Claim this listing to set pricing, connect Stripe payouts, and keep 70% of every sale.
Sign up to claim

About

Lessons

Overview

Captures hard-won knowledge into structured, reusable lesson files. When someone discovers a quirk, workaround, or "I wish someone had told me this" moment, this skill turns it into a lesson that others can learn from.

Keywords: lesson, create a lesson, generate a lesson, document this, write this up, what I learned, gotcha, quirk, workaround, TIL

How It Works

Step 1 — Gather the Facts

If the user hasn't provided details, ask these questions (skip any they've already answered):

  1. What happened? — What were you trying to do?
  2. What went wrong? (or what was unexpected)
  3. What did you discover? — The fix, workaround, or insight
  4. What should someone do instead? — The recommended approach

If the conversation already contains this context (e.g., they just debugged something with you), extract it automatically — don't make them repeat themselves.

Step 2 — Generate the Lesson

Write a markdown file using this exact format:

# [Title — clear, searchable, specific]

**Discovered**: [Month Year]
**Context**: [Tool/platform/language this applies to]

## The Problem

[1-2 paragraphs. What were you trying to do? What happened instead?
Include the exact error message or unexpected behavior if applicable.]

## What You'll See

[Show the actual output, error, or behavior. Code blocks with real examples.
This helps people recognize "oh, that's what's happening to me too."]

## The Fix

[Step-by-step solution. Code examples. Be specific enough that someone
can copy-paste and solve their problem.]

## Why This Happens

[Optional but valuable. The root cause — helps people understand,
not just follow instructions.]

## Recommendation

[One sentence: what to do going forward. The TL;DR.]

Step 2b — Extract Quirk Markers

After writing the lesson, extract technical quirks and add structured HTML comment markers. For EACH technical failure, bug, or gotcha in the lesson, add:

Rules:

  • Only extract TECHNICAL patterns (API quirks, code gotchas, platform constraints)
  • Do NOT create quirks for reflections, confidence, impact, or hypotheses
  • Place markers immediately after the relevant section
  • Tags should describe the technology (e.g., google-apps-script, python, openshift, rust)
  • Each marker should be self-contained

These markers enable automated quirk extraction via generate-quirks.py.

Step 2c — Generate Quirk Tag Files

After writing the lesson with QUIRK markers, also generate the corresponding quirk tag files in quirks/ using this format:

# [Tag Name] -- Technical Quirks

triggers: [comma, separated, trigger, keywords]
updated: [YYYY-MM-DD]
count: [number of quirks]

---

### [Quirk title]
**When:** [situation]
**Wrong:** [what fails]
**Right:** [what works]
**Why:** [root cause]
*Source: [lesson-filename.md]*

Rules for quirk files:

  • Group quirks by technology tag (one file per tag, e.g., snowflake.md, python.md)
  • If a tag file already exists, append new quirks and update the count
  • Triggers should be keywords that help someone find this quirk (tool names, error fragments, common terms)
  • Update _index.md with the new/updated tag files

Step 2d — Sanitize Personal Information

Before saving ANY lesson or quirk file, sanitize all personal information:

  • Replace real usernames with generic placeholders (e.g., YOUR_USER)
  • Replace real email addresses with user@example.com or manager@example.com
  • Replace real account identifiers with your-account-id
  • Replace resource IDs (Sheet IDs, project IDs, etc.) with YOUR_SHEET_ID, YOUR_SCRIPT_ID, etc.
  • Replace OAuth client IDs with YOUR_CLIENT_ID
  • Remove any API keys, tokens, bearer tokens, passwords, or secrets
  • Remove real person names used as examples — use generic titles instead
  • Keep product names, role patterns, and technical terms — only strip identifying info

Test: Run grep -rn -i -E "(your_real_username|your_real_email|client_secret|api_key)" lessons/ quirks/ before committing. Output should be empty.

Step 3 — Save and Share

Save the lesson file AND quirk tag files:

  1. Save lesson to your lessons directory (e.g., lessons/[slug].md)
  2. Save/update quirk tag files in quirks/
  3. Update quirks/_index.md

Then commit and push:

git add lessons/[filename].md quirks/
git commit -m "Add lesson + quirks: [title]"
git push

If generate-quirks.py exists in the repo root and runs as a hook, it will auto-regenerate the quirk tag files from QUIRK markers. In that case, only commit the lesson file and let the hook handle quirks.

Naming Convention

File names should be lowercase, kebab-case, and descriptive:

  • granite-tool-calling-quirks.md
  • openshift-sandbox-no-internet.md
  • internal-ssl-cert-errors.md
  • python-async-windows-event-loop.md

NOT: lesson1.md, notes.md, fix.md

Auto-Detection

If the user just finished debugging something with Claude and says any of these, trigger this skill:

  • "create a lesson about this"
  • "write this up as a lesson"
  • "document this for the team"
  • "generate a lesson"
  • "save this as a lesson"
  • "TIL" / "today I learned"
  • "someone else should know about this"
  • "I don't want anyone else to hit this"

Pull the problem, discovery, and fix from the conversation history — don't ask questions they've already answered.

Trigger Phrases

  • "create a lesson"
  • "generate a lesson"
  • "write a lesson about"
  • "document this"
  • "save this as a lesson"
  • "write this up"
  • "TIL"
  • "today I learned"

Tone

  • Practical: someone is reading this because they're stuck. Get to the fix fast.
  • Specific: exact error messages, exact commands, exact versions.
  • Honest: "We tried X and it didn't work" is valuable. Don't hide the failures.
  • Generous: write it for the person who will Google this at 11pm.

Direct Quirk Creation (without a lesson)

Quirks can also be created directly — without writing a full lesson first. This is for when the user says "create quirks" or "save these quirks" after a debugging session.

When to create quirks directly

  • After a debugging session where something non-obvious was discovered
  • When the user says "create quirks", "save quirks", "document these gotchas"
  • Proactively after hitting a technical pitfall during a build session
  • When the conversation contains enough context to extract quirks without a full lesson

Filing rules (critical — follow exactly)

  1. File by tool/technology — name the file after the tech: python.md, ollama.md, windows.md. NEVER name it after the project (no my-project-quirks.md).
  1. Add to existing tag files first — if python.md already exists, append your new quirk to it and increment the count: header. Only create a new tag file for a genuinely new technology.
  1. Update the index — after adding/creating quirk files, update _index.md:
  • Increment Total quirks: and Total tag files: counts
  • Add new tag file rows to the Tag Files table
  1. One quirk = one pitfall — each ### block covers exactly one thing. Don't combine multiple issues into one block.
  1. Be specific — include exact error messages, exact function names, exact commands. Someone should be able to ctrl+F their error and find the quirk.

Where quirks live

Quirks are stored in a quirks/ directory inside the user's training/enablement repo. Check the user's memory or ask them where their quirks repo lives. The directory contains:

  • _index.md — summary index with counts and trigger keywords
  • {technology}.md — one file per technology tag

Common mistakes to avoid

  • DO NOT save quirks to Claude Code auto-memory — they belong in the quirks repo
  • DO NOT create a CLAUDE.md in the project repo for quirks — use the dedicated quirks directory
  • DO NOT name quirk files after projects — name them after technologies
  • DO NOT create a new tag file when an existing one covers the same tech — append instead
  • DO commit and push quirks to the remote repo after creating them

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

No reviews yet, be the first.

Versions

  • v0.1.0 Imported from the upstream source.