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/danielpodolsky/ownyourcode/retrogit clone --depth 1 https://github.com/DanielPodolsky/ownyourcodeWhat 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 | $0.00014 | $0.02007 |
| Opus 5 | $0.00007 | $0.01004 |
| Sonnet 5 | $0.00003 | $0.00401 |
| Haiku 4.5 | $0.00001 | $0.00201 |
Grade A, and why
retro 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 — 329 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/own:retro
⚠️ PLAN MODE WARNING: Toggle plan mode off before running this command (
shift+tab). OwnYourCode commands don't work correctly with plan mode.
Extract learnings from completed work and persist them for future reference.
Overview
This command is run after completing work (typically after /own:done). It:
- Reflects on what was learned
- Documents patterns worth reusing
- Records failures to avoid
- Updates the learning registry
- Generates skill files for significant learnings
"The junior who documents their failures outgrows the senior who repeats them."
Execution Flow
Phase 1: What Did You Just Complete?
"What did you just finish working on?"
If they just ran /own:done, reference that context.
Get:
- Feature/task name
- Domain (auth, forms, API, etc.)
- Rough summary
Phase 2: Learning Extraction
Ask these questions to extract learnings:
Question 1: The Hard Part
"What was the hardest part of this work?"
Looking for:
- Technical challenges overcome
- Confusing concepts clarified
- Time-consuming debugging
Question 2: The Insight
"What do you know now that you didn't know before you started?"
Looking for:
- New understanding of a concept
- Better approach discovered
- "Aha!" moments
Question 3: The Pattern (if applicable)
"Did you discover or use a pattern that worked well? Something you'd want to reuse?"
Looking for:
- Code patterns worth extracting
- Approaches that solved problems elegantly
- Techniques to remember
Question 4: The Failure (most valuable)
"Did you make any mistakes or hit any walls? What went wrong before it went right?"
Looking for:
- Bugs that took time to find
- Wrong approaches tried first
- Misunderstandings that caused problems
Question 5: The Advice
"If you could go back and tell yourself one thing before starting this task, what would it be?"
This often captures the most actionable learning.
Phase 3: Categorize Learnings
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 · 329 lines · 14 tokens per session scan A 345590b896b6
retro is a command published in the GitHub repository DanielPodolsky/ownyourcode (276 stars, last pushed 2mo ago), licensed MIT. It adds 14 tokens to every session and 2,007 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 2026-08-30.
Other commands, from other repositories
output
Generate output artifacts from active wiki content — summaries, reports, study guides, slide outlines, timelines, glossaries, comparisons. Outputs are filed back into the wiki.
audit-quiz-coverage
Find quiz coverage gaps from recent guide/CHANGELOG/CC-releases changes and propose new questions.
retex
Retex - Capture lesson learned dans memory après fix, rollback, erreur.
al-memory-create
Generate or update memory.md file tracking decisions, changes, and learnings throughout project development for continuity across sessions. Use when you need to create or update memory, track decisions, or maintain session continuity.
dashboard
Launch the learning dashboard web UI to view and edit plans, progress, and spaced repetition data.
learn
Start learning a new topic — asks clarifying questions, researches resources, and creates a structured learning plan.