Skills DirectorySkills Directory
SkillsLearnSecurityCategoriesDocsCommunityBlog
Sign InSubmit Skill
Skills Directory

Security-tested agent skills for Claude, coding agents, and AI workflows.

Directory

  • Browse Skills
  • All Skills A–Z
  • Claude Skills
  • Claude Code Skills
  • Agent Skills
  • Categories
  • Submit a Skill

Learn

  • Learn Hub
  • Install Claude Skills
  • Write SKILL.md
  • Skills vs MCP
  • Directories Compared

Security

  • Security
  • Methodology
  • Secure Claude Skills
  • Security Badges

Company

  • About
  • Community
  • Blog
  • API Docs
  • Advertise

2026 Skills Directory. All rights reserved.

Back to skills

Spark Learner Engagement

ASecurity

The curriculum is mapped, the arc is set. The question now is whether the learner will finish. Load whenever you hear \"completion rates are bad,\" \"people start and stop,\" \"the cohort drops off after week two,\" or \"I shipped it and nobody finished.\"

6 stars
0 votes
0 copies
0 views
Added 9/20/2026
ai-agentsgo

Security Analysis

A100/100

Scanned 9/20/2026

Install to Claude Code

$npx -y skills add FerroxLabs/murage --skill spark-learner-engagement --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Spark Learner Engagement?

Add the live security badge to your README — it updates automatically with every re-scan.

Security grade badge for Spark Learner Engagement
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/ferroxlabs-spark-learner-engagement/badge)](https://www.skillsdirectory.com/skills/ferroxlabs-spark-learner-engagement)

More formats (shields.io, HTML) on the badges page.

Download Zip
Files
SKILL.md
---
name: spark-learner-engagement
description: "The curriculum is mapped, the arc is set. The question now is whether the learner will finish. Load whenever you hear \"completion rates are bad,\" \"people start and stop,\" \"the cohort drops off after week two,\" or \"I shipped it and nobody finished.\""
metadata:
  author: wayland
  version: "1.0.0"
  category: "spark"
---

# Learner engagement

## When to load this mode

The curriculum is mapped, the arc is set. The question now is whether the learner will finish. Load whenever you hear "completion rates are bad," "people start and stop," "the cohort drops off after week two," or "I shipped it and nobody finished."

## Procedure

Completion is a design problem, not willpower. Most courses lose the learner because the next step was too big, the first win came too late, or the learner forgot why they enrolled. Four interventions, designed in during the build.

**1. Engineer a first win inside the first session.** Per B.J. Fogg's Tiny Habits research, behavior repeats when the first instance is small, easy, immediately rewarded. The first lesson must produce one artifact the learner can show themselves within twenty minutes.

Not a quiz score. An artifact: a sentence written, a message sent, a decision made. Same shape as the final transformation, smaller. If the course ends with a discovery call, the first-session artifact is one sentence of the opener. If the book ends with a manuscript, the first chapter ends with one paragraph drafted.

The first win proves the format works and makes quitting cost the learner something they already made.

**2. Space the retrieval; don't mass the practice.** The spacing effect: information practiced across spaced intervals sticks better than the same time in one block. Mass-practice feels productive and forgets fast.

Two moves:

- **Open each session with a retrieval prompt from a prior session, not a recap.** Recap is recognition. Retrieval is production. A three-question retrieval at session four beats fifteen minutes of review.
- **Schedule module N's assessment inside module N+2.** Forces retrieval under realistic delay.

Don't announce the strategy. Learners optimize against the test. Build it into the structure.

**3. Remove friction from the next step.** Drop-off concentrates at session transitions. Three interventions:

- **End each session with the next action in one sentence the learner can do in under fifteen minutes.** "Read chapter four" is too big. "Open chapter four and underline the one sentence that names your situation" is right-sized.
- **Open the next session with the learner's last artifact, not a new topic.** Continuity at the seam beats novelty.
- **Eliminate "where was I."** A two-line "you were here, you are going here" header on every session. A learner returning after three days finds their place in five seconds.

**4. Build accountability scaffolding the format can carry.** Different formats afford different accountability. Match honestly.

- **Self-paced.** Public commitment at enrollment. Email check-ins at session boundaries. Optional artifact submission with template feedback.
- **Cohort.** Weekly live session, one named outcome each. Peer-pair (each learner assigned one peer). Public artifact wall — visible work pulls in late learners and signals norms.
- **Book.** Reader-action prompts at chapter ends. One companion artifact (template, checklist, worksheet). An author-side touchpoint if scale allows.

Pick the lightest scaffolding that holds. Over-promised community is worse than honestly self-paced.

## Decision rules

- **First win in the first session, or the first session is wrong.** Cut content until the learner produces something inside twenty minutes.
- **Every session ends with one fifteen-minute next action.** No exceptions. Vague endings are the largest single driver of drop-off.
- **Retrieval, not recap.** If a review section can be answered by recognition, rewrite as production.
- **Match accountability to format honestly.** A self-paced course pretending to be a cohort is worse than one that owns it.
- **Measure completion, not engagement metrics.** Time-on-page and video-watch percentage are vanity. Final artifact is the only number that matters.

## Anti-patterns

- **Gamification as completion strategy.** Badges, streaks, points layered on a course nobody wanted to finish. Treats a design problem as motivation.
- **Front-loading theory.** Three sessions of foundations before the learner does anything. Drop-off is highest right here.
- **Massed practice in one block.** "Do all the exercises at the end of the module." Feels efficient, forgets in a week.
- **Promising community you don't moderate.** A Slack channel silent in week two does more damage than no community.
- **Optimizing engagement metrics.** Time-watched, scroll-depth, lesson-opens. Learners game these and still don't finish.

## Before / after

**Before:** *"The course has eight modules of two-hour videos. We added a quiz at the end of each module and a private Facebook group. Most people drop off after module two."*

**After:** *"Module one ends with the learner sending one outreach message to a real prospect — twenty minutes, before they close the tab. Module two opens with a three-question retrieval on module one, then assesses it under delay. Every session ends with one fifteen-minute action and a two-line header. The Facebook group becomes peer-pair: each enrollee gets one peer. Completion measured as artifacts produced, not videos watched."*

Attribution

FerroxLabsFerroxLabs
View sourceMore from FerroxLabs →
SSkills DirectorySkills Directory

Your tool, in front of Claude Code builders.

3 founder slots · $299/mo · GSC-verified traffic · sponsors can never buy grades.

See placements

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments (0)

No comments yet. Be the first to comment!

SSkills DirectorySkills Directory

Your tool, in front of Claude Code builders.

3 founder slots · $299/mo · GSC-verified traffic · sponsors can never buy grades.

See placements

Related Skills

Caveman

Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.

1023331 votes

Hyperplan

Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...

686011 votes

Mcp Code Execution

Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.

3331 votes

catchup

Recovers prior coding-agent session context by running `catchup <agent> --since-compact`, which extracts a clean summary of a previous Codex, Claude Code, Antigravity, OpenCode, or Pi Agent session. Use when the user says "catch up", "what did the last session do", "get me up to speed", "I switched agents", or asks to recover/summarize a previous session before continuing. Do NOT use for the current conversation, git history, or any non-agent log.

611 votes

math-skill

A comprehensive mathematical reasoning skill for AI assistants — handles arithmetic to research-level problems with rigorous step-by-step reasoning, systematic verification, and transparent uncertainty handling

381 votes
View all in ai-agents →