drop another .md file to compare - side-by-side diff against course

course

Lays out the structure for a course you want to teach.

description: "Triggers on prompt mention of 'course'."

personal 2 files 10 recent evals

Export

What it does for you

Lays out the structure for a course you want to teach.

What it produces

A recent result, so you can see the kind of work it returns.

loading…

How to get it

These run inside the Snappy workspace. Want this working in your business? I set skills like this up with you, in one focused week.

Work with me

For developers how this skill is built, graded, and how it runs

at a glance- the short version

actorExported functions in state/lib/course.ts.

auditorNone wired yet - eval is manual (Robert review).

eval modeshape

categoryContent

stages3

what's inside - the parts that make up a skill 3/4 present

A skill is just a few plain-text files. Only the main one is required. The rest are optional, added as the work needs them. This is what the skill is made of; how it runs is just below.

The skill

state/skills/course/SKILL.md present

the skill itself, in plain text

The main file. It says what the skill is and lays out the steps in plain English.

Code

state/lib/course.ts present

code the skill can run

Reusable code this skill can call when it needs to.

Scripts

state/bin/course/ not present

helper scripts

Optional. Added when a skill has a few commands to run.

Loader

state/skills/course/AGENTS.md present

what the AI loads on the fly

Loaded automatically the moment this skill is needed. Kept short on purpose.

how it's graded - what counts as a good run 4 criteria · 3 deterministic · 1 judge

Each row is one thing a good run has to get right. deterministic means a quick check decides, pass or fail. judge means the AI reads the result and rates it. Grading each piece on its own (instead of one overall score) shows exactly where a run fell short, so the fix is obvious.

name

kind

check

calls_get_modules_function

deterministic

The execution log includes a call to the 'getModules()' function.

calls_get_course_module_function

deterministic

The execution log includes a call to the 'getCourseModule()' function.

calls_get_slack_info_function

deterministic

The execution log includes a call to the 'getSlackInfo()' function.

course_function_output_quality

judge

The output from the 'course' skill, based on the calls to its constituent functions, accurately and completely reflects the expected course structure and information.

how it runs - the shared frame every skill uses 5/5 present

Every skill runs the same way. One part does the work, a separate part checks it, and a short loader hands the AI exactly what it needs for the job. Anything this skill doesn't use shows a one-line note saying why, on purpose, not by accident.

makes the work The worker

present

Exported functions in state/lib/course.ts. the worker

Does the actual work. Whatever it produces is what gets checked next.

checks the work The reviewer

present

None wired yet - eval is manual (Robert review). the checker

A separate checker grades the work, so the part that made it can't approve its own work.

frame

learns Self-correction

present

fixes itself learns from gaps

When a run hits a gap, the skill gets edited on the spot [FIXED] or queued for a bigger rewrite [LOGGED], so it keeps getting better.

tidies up Background fixes

present

queued for rewrite runs in the background

Bigger fixes that can't be made on the spot get queued and rewritten in the background later.

remembers Run history

present

state/log/pending-eval.ndjson pending runs

Every run is written down here, then reviewed by hand each week.

Critical rules the things this skill must not get wrong

NEVER use fake certificates or gamification language. Value is understanding the SHAPE of the tech; lessons teach architecture readers can imagine, never "claim your certificate." (feedback_no_fake_certificates.md)
The course lives in Skool, not Slack. There's no separate Slack group — it's built inside the existing Skool community. (project_course_skool_not_slack.md)
Course images must use the 6-layer template — never freehand. (feedback_image_quality_standard.md)
Courses are documentation that teaches — Skool explains, gateway links serve live skill files; courses force system clarity. (project_courses_as_documentation.md)

what it has learned - fixes written back in over time sample

When a run hits something this skill didn't handle, the fix gets written back into the skill so it doesn't happen again. FIXED means it was corrected on the spot. LOGGED means it's queued for a bigger rewrite. Either way, the skill gets a little better and never makes the same mistake twice.

Loading feedback rows…

how the work flows- who makes it, who checks it

actor Exported functions in state/lib/course.ts.

1 generator

invoke

actor = Exported functions in state/lib/course.ts.

import from `state/lib/course.ts` — `getModules()`, `getCourseModule()`, `getSlackInfo()

+ eval for this step

auditor None wired yet - eval is manual (Robert review).

2 auditor

inspect

auditor = None wired yet - eval is manual (Robert review).

getModules()` lists current modules before any update

+ eval for this step

3 data

eval log

`state/log/pending-eval.ndjson` (manual eval — skill: "course")

+ eval for this step

SKILL.md- the skill, written out in plain English

course

Free agentic-building course structure.

Ported from kernel snappy-course in Phase 0.5. See state/lib/course.ts for the full API surface.

Steps

getModules() - see state/lib/course.ts
getCourseModule() - see state/lib/course.ts
getSlackInfo() - see state/lib/course.ts

Eval

Actor: the exported functions in state/lib/course.ts. Auditor: none wired yet - eval is manual (Robert review). File a state/log/pending-eval.ndjson row on each run.

Score convention:

Outcome	Score
Pass on first try	1.0
Failed first, auto-fix applied, re-check passed	0.5
Still failing or unrecoverable	0.0

Gotchas

via the Phase 0.5 driver. Only these rewrites were applied: already in state/lib/)

realpathSync(process.argv[1]) CLI guard wrapped in try/catch

See the kernel SKILL.md for the original long-form guidance if you need it

(read-only reference at the kernel path above).

Graduation

This skill is prose. Graduate by defining a deterministic auditor and flipping eval: auto.

Rubric

criteria:
  - name: calls_get_modules_function
    kind: deterministic
    check: "The execution log includes a call to the 'getModules()' function."
  - name: calls_get_course_module_function
    kind: deterministic
    check: "The execution log includes a call to the 'getCourseModule()' function."
  - name: calls_get_slack_info_function
    kind: deterministic
    check: "The execution log includes a call to the 'getSlackInfo()' function."
  - name: course_function_output_quality
    kind: judge
    check: "The output from the 'course' skill, based on the calls to its constituent functions, accurately and completely reflects the expected course structure and information."

AGENTS.md- what the AI loads when this skill comes up

course - loader

Per-turn rules for the course skill. Full reference: state/skills/course/SKILL.md. Do not skip these.

Critical Rules

NEVER use fake certificates or gamification language. Value is understanding the SHAPE of the tech; lessons teach architecture readers can imagine, never "claim your certificate." (feedback_no_fake_certificates.md)
The course lives in Skool, not Slack. There's no separate Slack group - it's built inside the existing Skool community. (project_course_skool_not_slack.md)
Course images must use the 6-layer template - never freehand. (feedback_image_quality_standard.md)
Courses are documentation that teaches - Skool explains, gateway links serve live skill files; courses force system clarity. (project_courses_as_documentation.md)

Commands

| ui dashboard | state/skills/course/resources/ui.openui | |invoke: import from state/lib/course.ts - getModules(), getCourseModule(), getSlackInfo() |verify: getModules() lists current modules before any update |eval log: state/log/pending-eval.ndjson (manual eval - skill: "course")

OpenUI Resource

Skill-owned OpenUI Lang resource: state/skills/course/resources/ui.openui. Read it before rendering or editing this skill's generated component surface.
Treat this resource as a first-class artifact of the skill, not a generic chat response. Improve it when the skill's user-facing output needs to become richer.
System resources compose OpenUI primitives and inherit SnappyChat tokens. Use ui_contract: branded in SKILL.md only for deliberate platform or client visuals.

Known Pitfalls

getSlackInfo() is a legacy fn - the actual community is Skool; treat Slack info as historical/secondary
Skool sidebar is flat (~10 ordered courses target), not a category tree. Don't model around categories. (project_skool_no_categories.md)
Claude Partner Network requires 10 people complete 4 Skilljar courses to activate - course completions matter (project_claude_partner_program.md)

Self-Test

An agent reading this should correctly:

[ ] Refuse to add "claim your certificate" language to a lesson
[ ] Place new course content in Skool, not propose a new Slack group
[ ] Use the 6-layer image template for any course illustration

Self-report

If this loader fell short, append a line:

echo "[$(date -u +%FT%TZ)] course: <what was missing>" >> state/log/loader-feedback.log

Self-correcting loader (PID feedback)

This is the rule that makes loaders learn. Ported from snappy-kernel, where it demonstrably worked: the snappy-dom-cartographer skill mapped Skool admin UI once, every later ship-agent inherited the full map for free.

Before you finish, do two things:

1. Fix gaps (P - proportional). MANDATORY. If this loader didn't cover your case - if you had to read another file, run an undocumented command, work around a wrong selector, or discover a quirk - you MUST attempt an Edit to this AGENTS.md before you log.

Default action: edit this file. Surgical. Add the missing line, table

row, or code example where it belongs. No restructuring.

Only LOGGED is allowed when: the fix needs >10 lines, spans multiple

files, or requires a structural rewrite. In that case the state/regen/drain.sh queue picks it up asynchronously.

"I didn't have time" / "it's minor" / "the next agent will figure it out"

are NOT valid reasons. Minor gaps compound - that's the whole point of this loop.

Concrete example of a valid P-fix: discover agent-browser screenshot

takes path positionally not as --output <path>. One line in a table. Edit it in. Do not just log it.

The goal: the next agent never has to leave the loader.

2. Log the result.

echo "[$(date -u +%FT%TZ)] course: <what was missing or fixed> [FIXED|LOGGED]" >> state/log/loader-feedback.log

FIXED = you patched this loader inline (P-fix).
LOGGED = too large for inline; the PostToolUse enqueue + Stop-hook drain

will rewrite the loader from scratch on next session-end.

Do not skip this. Every agent run must leave the system better than it found it. The loader is the setpoint; you are the sensor; the gap is the error signal; closing the gap is the correction.

api.ts- the code it can call

#!/usr/bin/env npx tsx
/**
 * snappy-course/api.ts -- Free agentic-building course structure.
 *
 * Reads course content map from SKILL.md. Pure data skill -- no external APIs.
 *
 * Usage:
 *   npx tsx api.ts modules        # list all modules
 *   npx tsx api.ts module <id>    # specific module (1-3)
 *
 * Or import as module:
 *   import { getModules, getCourseModule } from "./course.ts";
 */

import { env } from "./env.ts";
import { realpathSync } from "fs";

interface Lesson {
  number: number;
  title: string;
}

interface Module {
  id: number;
  title: string;
  lessons: Lesson[];
}

const MODULES: Module[] = [
  {
    id: 1,
    title: "Build and control your first agent",
    lessons: [
      { number: 1, title: "What agentic building actually is" },
      { number: 2, title: "Your stack: Claude Code + skills + MCPs" },
      { number: 3, title: "Ship something today: a 30-minute agent" },
    ],
  },
  {
    id: 2,
    title: "Skills, MCPs, and the agentic stack",
    lessons: [
      { number: 1, title: "What a skill is and why it changes everything" },
      { number: 2, title: "MCPs in plain English: tools your agent can call" },
      { number: 3, title: "Wiring Claude Code to your codebase" },
    ],
  },
  {
    id: 3,
    title: "Control: keep agents from going off the rails",
    lessons: [
      { number: 1, title: "Plans, tasks, and verification -- the control loop" },
      { number: 2, title: "When to let the agent run and when to stop it" },
      { number: 3, title: "Reading agent output like a code review" },
    ],
  },
];

const PLANNED_MODULES = [
  "Xano + agents -- building a backend an agent can actually drive",
  "Skills as the OS -- writing, scoping, and chaining your own skills",
  "Shipping -- putting one real system into production with agents doing the work",
];

// --- Public API ---

export function getModules(): { live: Module[]; planned: string[] } {
  return { live: MODULES, planned: PLANNED_MODULES };
}

export function getCourseModule(id: number): Module | null {
  return MODULES.find((m) => m.id === id) || null;
}

export function getSlackInfo(): {
  teamId: string;
  subdomain: string;
  channels: { name: string; purpose: string }[];
} {
  return {
    teamId: "T0AQPFMQEKB",
    subdomain: "snappyclaudec-qdk8925.slack.com",
    channels: [
      { name: "#welcome", purpose: "New-member intro thread, pinned start-here post" },
      { name: "#lessons", purpose: "One thread per published lesson" },
      { name: "#wins", purpose: "Members posting things they shipped" },
      { name: "#help", purpose: "Stuck moments -- answered within 24h" },
      { name: "#live", purpose: "Announcements for live sessions and replays" },
      { name: "#general", purpose: "Default fallback, low-traffic" },
    ],
  };
}

// --- CLI ---

if ((() => { try { return import.meta.url === `file://${realpathSync(process.argv[1])}`; } catch { return false; } })()) {
  (async () => {
    const [, , cmd, ...args] = process.argv;

    switch (cmd) {
      case "modules": {
        const { live, planned } = getModules();
        console.log("Live modules:");
        for (const m of live) {
          console.log(`\n  Module ${m.id} -- ${m.title}`);
          for (const l of m.lessons) {
            console.log(`    ${l.number}. ${l.title}`);
          }
        }
        console.log("\nPlanned (not yet built):");
        for (const p of planned) console.log(`  - ${p}`);
        break;
      }
      case "module": {
        const id = parseInt(args[0], 10);
        if (!id) { console.error("Usage: api.ts module <id>"); process.exit(1); }
        const m = getCourseModule(id);
        if (!m) { console.error(`Module ${id} not found. Live modules: 1-3.`); process.exit(1); }
        console.log(`Module ${m.id} -- ${m.title}`);
        for (const l of m.lessons) {
          console.log(`  ${l.number}. ${l.title}`);
        }
        break;
      }
      default:
        console.log("Usage: npx tsx api.ts [modules|module] ...");
    }
  })();
}

scripts- helper scripts it can run

prose-only skill - 1 inline code block live in SKILL.md above (no state/bin/ sidecar yet).

how we check it- the checks, plus the last 10 runs

rubric shape schema-shape check (no inline rubric)

recent mean 1.00 · 10 runs actor/auditor: unverifiable

deps none declared

timestamp	verb	score	primary_issue	artifact
2026-04-25 04:11Z	-	1.00	-	-
2026-04-21 15:58Z	-	1.00	-	-
2026-04-21 15:56Z	-	1.00	-	-
2026-04-21 03:53Z	-	1.00	-	-
2026-04-25 04:11Z	-	1.00	-	-
2026-04-21 15:58Z	-	1.00	-	-
2026-04-21 15:56Z	-	1.00	-	-
2026-04-21 03:53Z	-	1.00	-	-
2026-04-25 04:11Z	-	1.00	-	-
2026-04-21 15:58Z	-	1.00	-	-