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.
git clone --depth 1 https://github.com/Dkm0315/frappe-agentWrote 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/dkm0315/frappe-agent/frappe-lms)<a href="https://agentmods.dev/commands/dkm0315/frappe-agent/frappe-lms"><img src="https://agentmods.dev/badge/commands/dkm0315/frappe-agent/frappe-lms/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/dkm0315/frappe-agent/frappe-lms"><img src="https://agentmods.dev/badge/commands/dkm0315/frappe-agent/frappe-lms.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00000 | $0.00063 |
| Opus 5 | $0.00000 | $0.00032 |
| Sonnet 5 | $0.00000 | $0.00013 |
| Haiku 4.5 | $0.00000 | $0.00006 |
Grade A, and why
frappe-lms 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 11d 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
Frappe LMS
Treat the task as Frappe LMS work.
- Identify learner, instructor, evaluator, and admin roles.
- Separate course, batch, lesson, quiz, assignment, assessment, enrollment, progress, and certificate concerns.
- Protect learner data, grading, enrollment, and assessment permissions.
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.
- 11d ago First seen · 8 lines · 0 tokens per session scan A e2ab0738324f
frappe-lms is a command published in the GitHub repository Dkm0315/frappe-agent (24 stars, last pushed 4d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 63 tokens. 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
workflow-guide
Pedagogical onboarding helper that explains which command and editor mode should be used now, why, and the next 2-3 steps in a practical way for users still learning the workflow phases. Heavier than what-next; the heavier sequence is justified only when the user wants to understand the workflow, not just the next…
gentle-sdd-onboard
Guided SDD walkthrough — onboard a user through the full SDD cycle using their real codebase.
sdd-apply
Implement SDD tasks — writes code following specs and design.
sdd-init
Initialize SDD context — detects project stack and bootstraps persistence backend.
icpg-bootstrap
Infer ReasonNodes from existing git commit history. One-time setup for existing codebases.
ijfw-audit
Run the IJFW audit gate for the current workflow phase. Usage: /ijfw-audit [phase name].