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/frankxai/agentic-creator-os/opsgit clone --depth 1 https://github.com/frankxai/agentic-creator-osWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/frankxai/agentic-creator-os/ops)<a href="https://agentmods.dev/commands/frankxai/agentic-creator-os/ops"><img src="https://agentmods.dev/badge/commands/frankxai/agentic-creator-os/ops.svg" alt="Measured on agentmods" height="20"></a>What 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 | $0.00035 | $0.00410 |
| Opus 5 | $0.00017 | $0.00205 |
| Sonnet 5 | $0.00007 | $0.00082 |
| Haiku 4.5 | $0.00003 | $0.00041 |
Grade A, and why
ops 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 yesterday.
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
/ops — Weekly Operations Loop
The execution layer of the FrankX Operations System. One command surfaces everything that needs attention across the business and drives each item one step forward.
Loads the ops skill (skills/ops/SKILL.md).
Usage
/ops # full loop: inbox · pipeline · PRs · content
/ops inbox # just triage new inquiries + draft replies
/ops pipeline # just advance CRM stages
/ops prs # just sweep open PRs across both repos
What it does
- Inbox — pull
Newinquiries from the Notion Inquiries CRM (or/admin/intake), classify urgency, draft replies in Frank's voice, advanceNew → Triaged. - Pipeline — advance
Triaged / Call booked / Proposalrows; flag anything stuck > 14 days. - PRs — list open PRs in
frankxai/frankx.ai-vercel-websiteandfrankxai/agentic-creator-os; build a merge queue + a fix queue. - Content — what shipped, what's queued, one recommended next piece (feeds
the
/build-logflywheel).
Guardrails
- Never auto-send a reply or close a deal without confirmation. Draft and propose.
- Voice: technical authority. Lead with the answer, link the artifact.
- If the pipeline is empty or PRs are clean, say so. No invented busywork.
See docs/ops/OPERATIONS_SYSTEM.md (website repo) for the full architecture and
the capture/acknowledge/track layers this loop sits on top of.
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.
- yesterday First seen · 43 lines · 35 tokens per session scan A b695fd356550
ops is a command published in the GitHub repository frankxai/agentic-creator-os (10 stars, last pushed yesterday), licensed Apache-2.0. It adds 35 tokens to every session and 410 once invoked, about $0.0002 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 2026-09-03.
Other commands, from other repositories
plan-okrs
Brainstorm team-level OKRs aligned with company objectives — qualitative objectives with measurable key results.
pre-mortem
Run a pre-mortem risk analysis on a PRD, launch plan, or feature — identify what could go wrong before it does.
stakeholder-map
Map stakeholders on a Power × Interest grid and create a tailored communication plan.
write-prd
Create a comprehensive Product Requirements Document from a feature idea or problem statement.
write-stories
Break a feature into backlog items — user stories, job stories, or WWA format with acceptance criteria.
retro
Facilitate a post-launch or sprint retrospective anchored to OKRs.