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/carlvellotti/free-ai-coursesWrote 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/carlvellotti/free-ai-courses/start-1-7)<a href="https://agentmods.dev/commands/carlvellotti/free-ai-courses/start-1-7"><img src="https://agentmods.dev/badge/commands/carlvellotti/free-ai-courses/start-1-7/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/carlvellotti/free-ai-courses/start-1-7"><img src="https://agentmods.dev/badge/commands/carlvellotti/free-ai-courses/start-1-7.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 | $0.00101 |
| Opus 5 | $0.00000 | $0.00051 |
| Sonnet 5 | $0.00000 | $0.00020 |
| Haiku 4.5 | $0.00000 | $0.00010 |
Grade A, and why
start-1-7 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 12d 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.
The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
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.
- 12d ago First seen · 9 lines · 0 tokens per session scan A 391d302fb581
start-1-7 is a command published in the GitHub repository carlvellotti/free-ai-courses (2,174 stars, last pushed 1mo ago), with no licence file. It costs nothing until one of its globs matches a file; then it loads 101 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
learn-pending
List all staged learning changes awaiting approval.
learn
Learn Claude Code best practices and capture lessons into persistent memory.
train-executor
Generate an executor onboarding playbook from a person's Freedom Path DELEGATE bucket. Produces SOPs in the person's voice, a training curriculum, and outdated-material flags. Non-technical-friendly — designed for Claude Desktop + Cowork usage.
training-coach-trainer
Train-the-trainer (TtT) protocol for internal subject-matter-experts who will deliver a training program. Condensed adult-learning principles, facilitation skills, common SME-as-trainer failure modes, cohort facilitation practice schedule, and a TtT-readiness rubric. Refuses SME deployment without TtT.
training-curriculum
Outcome-back curriculum design for a single program or module. Starts from the L3 job behavior change and L4 business outcome; works backward through capability requirements, sequencing, spaced retrieval, cognitive-load chunking, encoding-context simulation, and per-module evaluation rubric. Refuses content-first…
training-measure-transfer
Kirkpatrick L3 (behavior) + L4 (results) measurement plan for a training program. Behavior observation protocol with sampling cadence, business-metric tracking, post-program reinforcement plan, redesign feedback loop. Refuses L1-only smile-sheet evaluation; refuses programs without baseline.