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- Research Units Pipeline Skills
- Tutorial Spec
tutorial-spec_skill
- Python
109
GitHub Stars
1
Bundled Files
2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.
Installation
Preview and clipboard use veilstrat where the catalogue uses aiagentskills.
npx veilstrat add skill willoscar/research-units-pipeline-skills --skill tutorial-spec- SKILL.md3.8 KB
Overview
This skill produces a structured tutorial specification that locks scope, audience, prerequisites, measurable objectives, non-goals, and a single running example. It is the canonical starting artifact for any tutorial pipeline so downstream module planning and writing remain deterministic. The output is a concise, testable TUTORIAL_SPEC.md following a fixed template.
How this skill works
The skill reads required context from STATUS.md and optionally from GOAL.md and DECISIONS.md, extracting constraints such as time, depth, language, and pre-agreed limits. It generates a compact spec that includes audience, prerequisites, 3–8 measurable learning objectives, explicit non-goals, a consistent running example, and deliverable format. It enforces testability by rewriting vague objectives into observable outcomes and shrinking running examples that are too large.
When to use it
- At the start of a tutorial pipeline to lock scope before module planning (C1).
- When you need measurable objectives for exercise and assessment design.
- If STATUS.md contains constraints that must be respected by content authors.
- When GOAL.md or DECISIONS.md exist and must be respected in the tutorial scope.
- When converting a high-level topic into a deterministic, executable teaching plan.
Best practices
- Specify audience and prerequisites precisely (role, skill level, time availability).
- Write objectives with observable verbs (implement, debug, evaluate, explain).
- Choose one running example that is simple but non-trivial and fits end-to-end completion.
- Declare explicit non-goals to prevent scope creep and set expectations.
- Treat DECISIONS.md as authoritative for pre-agreed constraints and cite it in the spec.
Example use cases
- Turn a research project GOAL into a bounded tutorial spec for a hands-on workshop.
- Create a spec for onboarding new contributors to a codebase with measurable coding tasks.
- Define a short tutorial for implementing and evaluating a small agent variant.
- Prepare a classroom lab spec where each module has verifiable checkpoints.
- Convert broad topic notes into a single-page spec for downstream writers and reviewers.
FAQ
STATUS.md is required. GOAL.md and DECISIONS.md are optional but used if present; DECISIONS.md overrides conflicting constraints.
How do you keep the running example finishable?
Pick the minimal end-to-end scenario that exercises core concepts, limit dataset size, and scope deliverables to a few files or a short script so exercises can verify outcomes.