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Lesson Plan

skill-yugash007-edu-agent-skills-lesson-plan · by yugash007

Use when structuring a multi-session learning roadmap with milestones, gates, and pacing calibrated to learner level and goal.

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Install

$ agentstack add skill-yugash007-edu-agent-skills-lesson-plan

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Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Purpose

Create a coherent learning roadmap that sequences sessions, defines milestones with verifiable gates, and prevents random topic jumping. Gives the learner a clear path from current level to stated goal.

Activation

  • Learner has a defined goal + time constraint ("interview in 2 weeks", "learn this repo in a month"). Multiple sessions planned with non-trivial sequencing. repo-understand produced a curriculum map needing personalization. Learner asks "where do I start and how do I get to X?"
  • Skip if: one-off session with no continuity. Learner needs immediate help on a specific concept/bug. Plan already exists and is current.
  • Routing: run repo-understand and find-your-level first if repo context or level is unknown. Revise plan when: learner stalls 2+ sessions, goal changes, or weak areas accumulate faster than planned.

Inputs

  • Learner goal (specific, time-bounded), level (from find-your-level), available sessions/time budget, known constraints (weak areas, learning style), repo/domain scope.

Plan Structure

Three layers: Phases (thematic blocks) → Sessions (individual units with focus + gate) → Gates (acceptance criteria before advancing).

Workflow

  1. Decompose Goal — Restate as a specific, observable outcome (not "learn ML" but "train and evaluate a classifier on custom dataset"). Identify 3–5 sub-goals.
  2. Check Prerequisites — For each sub-goal: list prerequisites, check which are confirmed, flag gaps as early sessions.
  3. Define Phases — Group sub-goals into 2–4 phases. Each phase has a coherent outcome and takes 2–5 sessions. Order so each phase's output feeds the next.
  4. Sequence Sessions — Break each phase into sessions. Each has: primary topic, skill(s) to use, gate criterion. Max 2 heavy concepts per session.
  5. Set Gates — Measurable acceptance criteria per session: "can explain X mechanism," "passes challenge-generator at intermediate tier," "completes repo exercise." Gates prevent surface-level advancement.
  6. Add Buffers — 1 revision session per 4–5 sessions. Define re-plan triggers: 2 consecutive gate failures → revise plan.
  7. Get Buy-In — Present as a proposal. Ask: "Does this pacing feel right?" Adjust before finalizing.

Rules

  • DO: gates are non-negotiable — don't advance before gate is passed.
  • DO: prerequisite gaps always get sessions before dependent content.
  • DO: include buffer sessions and explicit re-plan triggers.
  • DO: present as proposal with learner input, not a mandate.
  • DON'T: pack more than 2 major concepts per session — cognitive overload kills retention.
  • DON'T: scope-creep beyond the stated goal — every session must link to a sub-goal.
  • DON'T: treat the plan as static — revise when real outcomes differ from projections.

Output

Responses should contain: goal + level + session budget, sub-goals, prerequisite status, phase breakdown (sessions with topics/skills/gates), buffer sessions, re-plan triggers, and proposal confirmation prompt. Format naturally.

Checklist

  • [ ] Goal is specific and observable.
  • [ ] Every session has an explicit gate.
  • [ ] No session has more than 2 major concepts.
  • [ ] Buffer sessions and re-plan triggers included.
  • [ ] Plan presented as proposal with learner confirmation.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.