learn

Original：🇺🇸 English

Translated

Capture knowledge manually into the flywheel. Save a decision, pattern, lesson, or constraint for future sessions. Triggers: "learn", "remember this", "save this insight", "I learned something", "note this pattern".

2installs

Sourceboshu2/agentops

Added on2026-02-17

NPX Install

npx skill4agent add boshu2/agentops learn

SKILL.md Content

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Learn Skill

YOU MUST EXECUTE THIS WORKFLOW. Do not just describe it.

Capture knowledge manually for future sessions. Fast path to feed the knowledge flywheel without running a full retrospective.

Execution Steps

Given

/learn [content]

:

Step 1: Get the Learning Content

If content provided as argument: Use it directly.

If no argument: Ask the user via AskUserQuestion: "What did you learn or want to remember?" Then collect the content in free text.

Step 2: Classify the Knowledge Type

Use AskUserQuestion to ask which type:

Tool: AskUserQuestion
Parameters:
  questions:
    - question: "What type of knowledge is this?"
      header: "Type"
      multiSelect: false
      options:
        - label: "decision"
          description: "A choice that was made and why"
        - label: "pattern"
          description: "A reusable approach or technique"
        - label: "learning"
          description: "Something new discovered (default)"
        - label: "constraint"
          description: "A rule or limitation to remember"
        - label: "gotcha"
          description: "A pitfall or trap to avoid"

Default to "learning" if user doesn't choose.

Step 3: Generate Slug

Create a slug from the content:

Take the first meaningful words (skip common words like "use", "the", "a")
Lowercase
Replace spaces with hyphens
Max 50 characters
Remove special characters except hyphens

Check for collisions:

bash

# If file exists, append -2, -3, etc.
slug="<generated-slug>"
counter=2
while [ -f ".agents/knowledge/$(date +%Y-%m-%d)-${slug}.md" ]; do
  slug="<generated-slug>-${counter}"
  ((counter++))
done

Step 4: Create Knowledge Directory

bash

mkdir -p .agents/knowledge

Step 5: Write Knowledge File

Path:

.agents/knowledge/YYYY-MM-DD-<slug>.md

Format:

markdown

---
type: <classification>
source: manual
date: YYYY-MM-DD
---

<content>

Example:

markdown

---
type: pattern
source: manual
date: 2026-02-16
---

# Token Bucket Rate Limiting

Use token bucket pattern for rate limiting instead of fixed windows. Allows burst traffic while maintaining average rate limit. Implementation: bucket refills at constant rate, requests consume tokens, reject when empty.

Key advantage: smoother user experience during brief bursts.

Step 6: Integrate with ao CLI (if available)

Check if ao is installed:

bash

if command -v ao &>/dev/null; then
  echo "✓ Knowledge saved to <path>"
  echo ""
  echo "To add this to the quality pool for review:"
  echo "  ao pool stage <path>"
  echo ""
  echo "Or let it auto-index on next /retro or /extract."
else
  echo "✓ Knowledge saved to <path>"
  echo ""
  echo "Note: Install ao CLI to enable automatic knowledge flywheel."
fi

Do NOT auto-run
ao pool stage
. The user should decide when to promote to the quality pool.

Step 7: Confirm to User

Tell the user:

Learned: <one-line summary from content>

Saved to: .agents/knowledge/YYYY-MM-DD-<slug>.md
Type: <classification>

This knowledge is now available for future sessions via /research and /inject.

Key Rules

Be concise - This is for quick captures, not full retrospectives
Preserve user's words - Don't rephrase unless they ask
Use simple slugs - Clear, descriptive, lowercase-hyphenated
Minimal frontmatter - Just type, source, date
No auto-promotion - User controls quality pool workflow

Examples

Quick Pattern Capture

User says:

/learn "use token bucket for rate limiting"

What happens:

Agent has content from argument
Agent asks for classification via AskUserQuestion
User selects "pattern"
Agent generates slug:
```
token-bucket-rate-limiting
```

Agent creates

.agents/knowledge/2026-02-16-token-bucket-rate-limiting.md

Agent writes frontmatter + content
Agent checks for ao CLI, informs user about
```
ao pool stage
```
option
Agent confirms: "Learned: Use token bucket for rate limiting. Saved to .agents/knowledge/2026-02-16-token-bucket-rate-limiting.md"

Interactive Capture

User says:

/learn

Agent asks for content and type, generates slug

never-eval-hooks

, creates

.agents/knowledge/2026-02-16-never-eval-hooks.md

, confirms save.

Gotcha Capture

User says:

/learn "bd dep add A B means A depends on B, not A blocks B"

Agent classifies as "gotcha", generates slug

bd-dep-direction

, creates file, confirms save.

Troubleshooting

Problem	Cause	Solution
Slug collision	Same topic on same day	Append `-2` , `-3` counter automatically
Content too long	User pasted large block	Accept it. /learn has no length limit. Suggest /retro for structured extraction if very large.
ao pool stage fails	Path wrong or ao not installed	Show error, confirm file was saved to .agents/knowledge/ regardless
Duplicate knowledge	Same insight already captured	Check existing files with grep before writing. If duplicate, tell user and show existing path.

The Flywheel

Manual captures feed the same flywheel as automatic extraction:

/learn → .agents/knowledge/ → /research finds it → future work is smarter

This skill is for quick wins. For deeper reflection, use

/retro

.

learn

NPX Install

Tags

SKILL.md Content

Learn Skill

Execution Steps

Step 1: Get the Learning Content

Step 2: Classify the Knowledge Type

Step 3: Generate Slug

Step 4: Create Knowledge Directory

Step 5: Write Knowledge File

Step 6: Integrate with ao CLI (if available)

Step 7: Confirm to User

Key Rules

Examples

Quick Pattern Capture

Interactive Capture

Gotcha Capture

Troubleshooting

The Flywheel