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/lglucas/ai-dev-operating-system/processizegit clone --depth 1 https://github.com/lglucas/ai-dev-operating-systemWhat 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 | $0.00050 | $0.00443 |
| Opus 5 | $0.00025 | $0.00221 |
| Sonnet 5 | $0.00010 | $0.00089 |
| Haiku 4.5 | $0.00005 | $0.00044 |
Grade A, and why
processize 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.
What it actually says
/processize
Codify a manually-validated workflow into a documented, partially-automatable process. Validate-then-automate, never the reverse.
Expected input
/processize
Optional arguments:
/processize task="<short name of the workflow>" runs="<number of times done manually>"
If arguments are omitted, the skill asks for them via the 5-question gate.
Actions
- Invoke the
processizeskill (.claude/skills/processize/SKILL.md). - Run the 5-question validation gate.
- If gate passes, generate
docs/processes/<slug>.mdfrom the skill's output template. - Hand off any required follow-up:
privacy-audit(personal data),/multi-ai-review(financial blast radius),cost-watchdog(planned automation). - Stop before implementing automation — defer to a sprint task.
When to use
- A task has been done manually 3+ times and is repeating.
- The user asks "vamos automatizar isso?" —
/processizeruns FIRST to check readiness. daily-standupflagged the same manual chore across 3+ sessions.- Before scheduling a cron, webhook, or autonomous agent loop that codifies a workflow.
When NOT to use
- Task has been done fewer than 3 times — keep doing it manually.
- One-off task — write a session log, not a process.
- The task is still being discovered (changes shape each run) — use brainstorming or
prototype-lab.
Cross-references
- Skill:
.claude/skills/processize/SKILL.md - Principle:
ETHOS.mditem 13. - Often paired with:
/multi-ai-review,privacy-audit,cost-watchdog.
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 · 49 lines · 50 tokens per session scan A 37e0716a836b
processize is a command published in the GitHub repository lglucas/ai-dev-operating-system (11 stars, last pushed 24d ago), licensed MIT. It adds 50 tokens to every session and 443 once invoked, about $0.0003 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
MIGRATE_DESIGN
Design doc for the migration tool PR. Author: Sol ([email protected]). Co-authored-by: wakesync.
sync-linear
Sync current work with Linear ticket status.
commit
智能生成 Git 提交信息并提交.
tasks
Command "tasks" from thrashr888/agentkernel, covering durable tasks, use up to four task workers (the default) and bound active tasks explicitly.
webapp-testing
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
create-issue
Transform feature descriptions, bug reports, or improvement ideas into well-structured GitHub issues.