Agent skill

tutorial-spec

Define tutorial scope, target audience, prerequisites, learning objectives, and a running example; output a tutorial spec for downstream planning. **Trigger**: tutorial spec, scope, audience, prerequisites, learning objectives, running example, 教程规格. **Use when**: tutorial pipeline 的起点(C1),需要先锁定教学目标与边界,再进入 concept graph / module planning。 **Skip if**: 你不是在做教程产出(或已经有明确且不允许改动的 tutorial spec)。 **Network**: none. **Guardrail**: 结构化 spec 优先;避免提前写长教程 prose(prose 在 C3)。

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Install this agent skill to your Project

npx add-skill https://github.com/WILLOSCAR/research-units-pipeline-skills/tree/main/.codex/skills/tutorial-spec

SKILL.md

Tutorial Spec

Goal: define an executable tutorial scope so downstream planning can be deterministic.

Role cards (use explicitly)

Curriculum Designer (scope guardian)

Mission: define what the tutorial will and will not do so planning and writing do not drift.

Do:

  • Specify audience and prerequisites precisely.
  • Write measurable learning objectives (verbs: implement, debug, evaluate, explain).
  • Define explicit non-goals to prevent scope creep.

Avoid:

  • Vague objectives ("understand", "get familiar").
  • A running example that is too large to finish end-to-end.

Instructor (teaching loop)

Mission: pick a running example and outputs that can be verified by exercises later.

Do:

  • Choose a consistent running example that reappears in every module.
  • State expected deliverables (format, language, approximate length).

Avoid:

  • Blog-post style prose without checkpoints/exercises.

Role prompt: Tutorial Spec Author

text
You are defining the spec for a tutorial.

Your job is to lock scope and teaching intent before writing content:
- audience + prerequisites
- measurable learning objectives
- non-goals
- running example (simple but non-trivial)
- deliverable format and constraints

Style:
- structured, low prose
- every item should be testable later via an exercise

Inputs

Required:

  • STATUS.md (context + constraints)

Optional:

  • GOAL.md (topic phrasing)
  • DECISIONS.md (any pre-agreed constraints)

Outputs

  • output/TUTORIAL_SPEC.md

Output template (recommended)

  • Audience (who this is for)
  • Prerequisites (what they must already know)
  • Learning objectives (3–8 measurable outcomes)
  • Non-goals (explicit out-of-scope)
  • Running example (one consistent example used throughout)
  • Deliverable format (Markdown/LaTeX, code language, expected length)

Workflow

  1. Extract constraints from STATUS.md (time, depth, language, audience).
    • If DECISIONS.md exists, treat it as authoritative for any pre-agreed constraints.
  2. If GOAL.md exists, reuse its topic phrasing/examples so the spec stays consistent.
  3. Propose a running example that can survive the whole tutorial (simple but non-trivial).
  4. Write output/TUTORIAL_SPEC.md using the template above.
  5. Ensure every learning objective is measurable (can be verified by an exercise later).

Mini examples (measurable objectives)

  • Vague: Understand tool calling.

  • Measurable: Implement a tool-calling loop with schema validation and demonstrate failure handling on two test cases.

  • Vague: Learn evaluation.

  • Measurable: Design an evaluation protocol (task, metric, budget) and run it to compare two agent variants.

Definition of Done

  • output/TUTORIAL_SPEC.md exists and is structured (not long prose).
  • Running example is concrete and consistent.
  • Objectives are measurable and match the intended audience.

Troubleshooting

Issue: objectives are vague (“understand X”)

Fix:

  • Rewrite as observable outcomes (“implement Y”, “explain trade-off Z”, “debug W”).

Issue: running example is too large

Fix:

  • Reduce to a minimal end-to-end scenario that still exercises the core concepts.

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