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/notque/vexjoy-agent/retrogit clone --depth 1 https://github.com/notque/vexjoy-agentWhat 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 | $0.00024 | $0.00414 |
| Opus 5 | $0.00012 | $0.00207 |
| Sonnet 5 | $0.00005 | $0.00083 |
| Haiku 4.5 | $0.00002 | $0.00041 |
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 3d 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.
What it actually says
Retro Knowledge System
Interact with the learning database: view stats, search entries, and graduate mature learnings into agents/skills.
Usage
/retro # Status overview (default)
/retro list # Display all accumulated knowledge
/retro search TERM # Full-text search across learnings
/retro graduate # Graduate mature knowledge into agents/skills
Subcommands
status (default)
Shows learning system health: entry counts, categories, graduation status, injection method.
list
Displays all accumulated knowledge grouped by category from the learning database.
search
Full-text search (FTS5) across all learnings. Returns results ranked by relevance.
graduate
AI-driven evaluation of mature learning entries for embedding into specific agents/skills. Queries design/gotcha entries, evaluates each for prescriptive readiness, drafts modifications to the target agent/skill, and applies after user approval.
Instructions for Claude
Call the Skill tool with retro. Pass the command argument through to select the subcommand.
Parse the argument to select the subcommand:
- No argument or "status" → run status subcommand
- "list" → run list subcommand
- "search TERM" → run search subcommand
- "graduate" → run graduate subcommand
All retro operations go through python3 ~/.claude/scripts/learning-db.py — never parse learning files manually.
Related
scripts/learning-db.py— Python CLI for all database operationshooks/session-context.py— Injects pre-built dream payload and high-confidence patterns at session startscripts/learning.db— SQLite database with FTS5 search index
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.
- 3d ago First seen · 51 lines · 24 tokens per session scan A 0c81fdcd9f09
retro is a command published in the GitHub repository notque/vexjoy-agent (417 stars, last pushed 3d ago), licensed MIT. It adds 24 tokens to every session and 414 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.
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👈 COMECE AQUI — a bússola da imersão. Mostra os 3 dias da sala e o próximo passo (não executa nada).
explain
Explain code, concepts, or system behavior with adjustable depth levels.
start-1
Claude Code 를 처음 쓰는 PM 이 "설치 → 도구 지도 이해 → CLAUDE.md 로 맥락 주기" 까지 직접 손으로 해보며 익히도록, 한 번에 한 단계씩 끌고 간다.
explain
Read a BPMN 2.0 .bpmn file and explain it in plain language.