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 skills add ericrisco/rsc-harness --skill course-storytellinggit clone --depth 1 https://github.com/ericrisco/rsc-harnessWrote 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/skills/ericrisco/rsc-harness/course-storytelling)<a href="https://agentmods.dev/skills/ericrisco/rsc-harness/course-storytelling"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/course-storytelling/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/skills/ericrisco/rsc-harness/course-storytelling"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/course-storytelling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00079 | $0.03396 |
| Opus 5 | $0.00039 | $0.01698 |
| Sonnet 5 | $0.00016 | $0.00679 |
| Haiku 4.5 | $0.00008 | $0.00340 |
Grade A, and why
course-storytelling 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.
How it starts
The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Course Storytelling — Make the Teaching Land
Take a concept the student would forget and turn it into one they can't unhear. Profile the learner first, then run every concept through the Expert Secrets machine: epiphany story → named model → grounded analogy → proof → do-this-now → the so-what.
This skill owns the teaching narrative: extracting what a course actually teaches, finding where it stays abstract, and rebuilding each concept so the realization happens in the student, emotionally, not just on the slide. It borrows Russell Brunson's Expert Secrets frameworks as a teaching methodology (this is method, not text reproduction).
Boundaries: course-builder decides what the course must prove — outcomes, assessment, module order — and hands you the skeleton; this skill makes each concept inside it land. presentations turns the landed lesson into a deck, design owns the pixels, marketing owns the words that sell the course, and a content-audit/review-content pass diagnoses an existing lesson (run it first, bring its findings here — that pass audits, this one rebuilds).
Teaching ≠ selling. Brunson's frameworks here serve comprehension and retention. The "sale" you're closing is belief in the idea and trust in the teacher — never bolt a pitch onto a lesson.
Learner grounding (hard gate — read this first)
Never reframe teaching without a complete learner + audience profile. Teaching into a void defaults to your AI-median explainer voice — abstract, jargon-true, emotionally dead. An incomplete profile is a hard STOP, not a warning, because everything downstream (which false belief to break, which analogy lands) is derived from it.
- Locate the profile. Read the root
CLAUDE.md, follow its## Knowledge mappointer to02-DOCS/wiki/index.md, and look for the entry into02-DOCS/wiki/teaching/(theharnessKarpathy-wiki convention: compiled articles in02-DOCS/wiki/teaching/, raw user-pasted material in02-DOCS/raw/teaching/). NoCLAUDE.md, no index entry, or a pointer that goes nowhere = ABSENT. - Check completeness against the checklist in
references/learner-grounding.md: the LEARNER (level, prior knowledge, pains, desires, current false beliefs, what they DO after), the AUDIENCE (same as the buyer? live vs recorded? size? context?), the target TRANSFORMATION (one result, before→after), and constraints/format. Any empty dimension = INCOMPLETE. - If ABSENT or INCOMPLETE, STOP and interview with the batched question script in
references/learner-grounding.md— one focused batch at a time, wait, persist, continue. Then write the profile as wiki articles under02-DOCS/wiki/teaching/(learner.md,audience.md,transformation.md,false-beliefs.md,constraints.md,index.md), save pasted transcripts/outlines/slides verbatim under02-DOCS/raw/teaching/and link them from each article's> Raw:line, index the profile in02-DOCS/wiki/index.md, and ensure rootCLAUDE.mdcarries the short pointer to that index (create it if absent; additive only). Article format and the exactCLAUDE.mdsnippet →references/learner-grounding.md. - Only then proceed, citing which articles you used ("grounded in
02-DOCS/wiki/teaching/learner.mdandfalse-beliefs.md") so every reframing is traceable to a real learner, not an imagined one.
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 138 lines · 79 tokens per session scan A fa4f372abc68
course-storytelling is a skill published in the GitHub repository ericrisco/rsc-harness (81 stars, last pushed today), licensed MIT. It adds 79 tokens to every session and 3,396 once invoked, about $0.0004 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 skills, from other repositories
tutorial
Interactive tutorial teaching Ouroboros hands-on.
eli5
Explain a topic like I'm a 5 year old — restate my last output, or a named topic, in plain words without dropping a single fact. Use when the user types /eli5 [topic], or says an answer was too technical, too long, or unclear about what he now has to do.
course-content-map
Refresh a safe, concise map of this GCI World 2026 workspace before deeper course, assignment, or dataset work.
analyzing-domains
Use when entering unfamiliar domains, modeling complex business logic, or when terms/concepts are unclear. Triggers: 'what are the domain concepts', 'define the entities', 'model this domain', 'DDD', 'ubiquitous language', 'bounded context'. Also invoked by develop during research phase.
merge-aliases
Folds two surface names for the same backend system into one canonical entity, keeping every original mention individually retrievable, and refuses to merge pairs that only share spelling.
anchor-and-lock
Consults a check that sits outside the loop system before finalizing any decision the frozen facts bear on, and refuses every attempt by a loop to rewrite a node marked frozen, regardless of how convergent the loop's own reasoning looks.