Researching one therapeutic indication and writing it up, with the indication treated as a patient population rather than a disease entity: who these patients are, how many of them there are, what is going wrong biologically, how they are treated today, what regulators have accepted before, and which trials shaped the field. Some populations do not map onto a billable diagnosis at all, and saying so is part of the job, because it changes the regulatory path. This is a research and writing recipe. It gives no medical recommendation, and nothing it produces has been checked against a verified evidence database.
The agent does the retrieval itself, and it has to reach current authoritative sources, cite them precisely, leave uncertainty and disagreement between sources on the page instead of smoothing them over, and obey the anti-fabrication gates the reference phases impose. No sidecar and no live data source ships with this Skill.
A Skill is a directory of files, so installing one is copying that directory
somewhere an agent looks. With Node 18+ and git on PATH (npm resolves a
github: spec through it), and nothing cloned:
npx github:PKU-YuanGroup/OpenAI4S install indication-dossier --target claude
--target claude writes to ~/.claude/skills, claude-project to
./.claude/skills, openai4s to <data_dir>/user-skills, and --dir <path>
to anywhere you name. The resolved absolute path is printed before anything is
written there, and --dry-run stops at that plan. A reinstall refuses to
overwrite a copy you have edited or one it did not install, and uninstall
removes only the files it wrote. For a recipe included in the npm release,
npx @pku-yuangroup/openai4s-skills install indication-dossier --target claude
installs the published copy. The npm catalog can differ from this repository.
Without Node, take the directory itself — and turn it into a .zip if an upload
field wants one. The tarball is the whole repository (over 100 MB), and the pipe
is a POSIX shell recipe (macOS, Linux, WSL) that extracts only this directory:
curl -L https://codeload.github.com/PKU-YuanGroup/OpenAI4S/tar.gz/refs/heads/main \
| tar -xz --strip-components=2 OpenAI4S-main/skills/indication-dossier
python3 -m zipfile -c indication-dossier.zip indication-dossier
The click-through form of that same download is the
repository zip,
which is also the route to take on Windows: extract it and copy
skills/indication-dossier/ out
(unzip main.zip 'OpenAI4S-main/skills/indication-dossier/*' unpacks only that
directory). If you already run OpenAI4S there is nothing to install — the wheel
ships every bundled Skill, and a bundled Skill takes precedence over a
same-named copy in <data_dir>/user-skills. Targets, provenance, and what the
installer refuses to do:
tools/skills-installer/.
| File | Responsibility |
|---|---|
SKILL.md |
Drives the run: five phases, each writing a waypoint file, with an identity check after Phase 1 and a resume path when the workdir already holds waypoints. It also fixes the inputs, the tools the Skill expects (and the fallback when an MCP is not connected), the output layout, and what the synthesis phase may still fetch rather than name as a gap. |
| Directory | Responsibility |
|---|---|
references/ |
Loaded on demand: the cross-phase research standards, one instruction file per phase, the writing style rules, and the JSON schemas for the waypoint files. |