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 commands/vladolaru/claude-code-plugins/learngit clone --depth 1 https://github.com/vladolaru/claude-code-pluginsWhat 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 | $0.00017 | $0.00875 |
| Opus 5 | $0.00009 | $0.00438 |
| Sonnet 5 | $0.00003 | $0.00175 |
| Haiku 4.5 | $0.00002 | $0.00088 |
Grade A, and why
learn 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 2d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/dex:learn
Capture a learning from the current conversation. Self-contained — extracts from chat history, no arguments needed. Optional focus hint narrows what to extract.
Step 1: Discover Project Infrastructure
Follow the Project Discovery steps from the knowledge-capture skill.
If .claude/docs/ does not exist, use AskUserQuestion:
Question: "No knowledge directory found. Create it?" Options:
- Yes, create
.claude/docs/— scaffoldslearnings/,patterns/,decisions/,research/ - Not now — abort capture
If "Not now", stop here. If "Yes", create directories with mkdir -p and continue.
Step 2: Extract Learning from Conversation
Run the <pre_extraction_analysis> from the knowledge-capture skill on the relevant conversation exchange. If $ARGUMENTS contains a focus hint, narrow extraction to that topic.
If the conversation contains nothing extractable as a learning (no discovery, fix, or gotcha), say so briefly and stop. Do not fabricate knowledge.
Following the Knowledge Extraction from Conversation guidance in the knowledge-capture skill:
- Identify the core insight — what's the one thing an agent should know next time?
- Draft a title as a short directive statement (e.g., "Always pass --user=1 for WP-CLI REST calls")
- Draft the Rule section — a specific, actionable directive: what to do and why, in 1-3 sentences
- Draft brief Context (why this matters, root cause) and Examples (correct vs. incorrect approaches)
- Identify 3-5 tags from the technical domain
- Determine the filename:
YYYY-MM-DD-slug.md
Verify the draft passes the <extraction_quality_checklist> from the knowledge-capture skill before presenting to the user.
Focus on the behavioral change: what should an agent do differently next time?
Step 3: Confirm with User
Use AskUserQuestion:
Question: "Capture this learning?"
Show exactly these fields in the question description:
Title: [drafted title] Rule: [1-2 sentence rule] File:
.claude/docs/learnings/YYYY-MM-DD-slug.md
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.
- 2d ago First seen · 92 lines · 17 tokens per session scan A 7b5cd883ad44
learn is a command published in the GitHub repository vladolaru/claude-code-plugins (8 stars, last pushed 4d ago), licensed MIT. It adds 17 tokens to every session and 875 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.