get-fsa-training-done

One agent skill, and the CLI behind it, for getting FSA training done: designing a programme, writing its teaching material, and designing and grading its assessments. It installs into Claude Code and the Codex CLI.

The landing page shows how it works, in real files; its source is in docs/.

The skill has three features, each with its own CLI namespace:

They divide one job. A programme's session plan names, in its Training Materials column, the file that serves each session — so program declares that a slot exists and what it weighs, material writes the lecture note or lab guide, and assessment writes the quiz, brief or exam. No feature authors another's artifact, and each checks its own half of that manifest.

The skill is built from tasks — one step each, such as writing a rubric, rendering a brief, or merging a retake — composed into workflows. Ask for a whole job and the agent follows the workflow; ask for one step and it runs that task on its own.

The skill is stateless. It assumes nothing about the directory layout it was installed into and never scans a project on a hunch — it asks for its inputs first, echoes back the resolved paths, and waits for a go-ahead.

Install

pip install get-fsa-training-done

This gives you the gftd command, which every example below uses; it is also installed under its full name, get-fsa-training-done. It needs Python 3.12+.

Then install the skill into your agent:

gftd install --platform all

Add --dry-run to any of install, update, or uninstall to see the exact file-by-file plan without touching anything.

Dependencies

Installing the package pulls nothing: dependencies = [] is deliberate, so the lifecycle commands run on a bare interpreter. The libraries the worker commands need live in the managed virtualenv instead — declared once in src/get_fsa_training_done/lifecycle/envmgr/requirements/core.txt:

gftd install builds that environment, so the first install needs a network and everything after it does not — which is the property that matters on an exam machine.

Two external tools are optional, and doctor reports each without failing for its absence:

• A .rar extractor (unar, 7z or bsdtar). .rar is proprietary and has no pure-Python reader; every other archive format is read in-process.
• Docker, for assessment sandbox: running a seed script, a JUnit suite or a pytest run that is not ours — an exam's supplied files, or a submission — in a disposable container with no network.

Rendering embeds its own fonts (see core/fonts/), so a Vietnamese brief comes out identical on every machine.

Layout

src/get_fsa_training_done/
  cli.py  skill.py          the CLI, and the one skill it installs
  lifecycle/                install, update, uninstall, status, doctor, env
  features/                 program, material, assessment (+ common)
  payload/get-fsa-training-done/
    SKILL.md                the router: workflows and tasks per feature
    references/<feature>/   overview, tasks/, workflows/, generated references
    references/common/      writing style, Vietnamese conventions, shared tasks

Development

pip install -e .
pytest
ruff check . && ruff format --check .
python scripts/sync_version.py --check
for generator in scripts/*/gen_*.py; do python "$generator" --check; done

src/get_fsa_training_done/__about__.py holds the canonical version; sync_version.py propagates it to the payload's VERSION.

Licence

MIT