Indication dossier
SkillMediaBuild a sourced research dossier for one therapeutic indication — patient population, epidemiology, disease biology, standard of care, regulatory path, and landmark trials. Use when the user asks for an indication overview, disease landscape, or trial-design background.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Indication dossier skill
What this skill tells your AI
The instructions your AI receives, as published by xuzhougeng/wisp-science in skills/indication-dossier/SKILL.md and read by ahel’s review.
Five research phases, each writing one waypoint JSON under
<workdir>/waypoints/, ending in a cited Markdown report. Waypoints make the
run resumable: a later invocation reads which files exist and continues from
the first missing one. The only pause for user input is after Phase 1.
The framing rule
Treat the indication as a patient population, not a disease entry. Every section answers a population question — who are these patients, how are they identified and managed, which trials would help them — rather than a textbook question about the condition. Nesting is population nesting: everyone in the child indication is in the parent.
Some inputs are not billable diagnoses at all: a biological state ("immunosenescence"), a non-accepted indication ("ageing"), an iatrogenic population ("GLP-1 induced sarcopenia"). Detect and label this early — it changes the epidemiology evidence base, the regulatory path, and what a "complete" dossier even looks like.
Inputs
| Input | Required | Meaning |
|---|---|---|
indication | yes | e.g. "sarcopenia", "idiopathic pulmonary fibrosis" |
additional_context | no | focus areas, parent indication, framing |
workdir | no | waypoint/report location; default ./do_not_commit/indication-dossier-<slug>/ |
Tooling
Preferred: clinical-trials MCP for CT.gov, pubmed MCP for literature,
WebSearch/WebFetch for FDA guidance, specialty-society guidelines
(NCCN, AASLD, …), and CDC/WHO data; WebFetch for remote PDFs, Read for
local ones; Agent subagents for parallel evidence gathering. When a listed
MCP is not connected, say so and fall back to WebSearch against the public
site itself.
Run protocol
Read references/standards.md first — it defines what counts as a citable
finding, the anti-fabrication rules, and the report style. Phase-by-phase
instructions live in references/phases.md; waypoint formats in
references/waypoints.md.
- Identity. Resolve definition, ICD codes, aliases, parent, diagnostic
status; quick CT.gov landscape count. Write
meta.json. Then show the resolved identity and end the turn asking Proceed / Revise identity / Stop — the expensive phases wait for the answer (Wisp has no separate interactive-question tool, so this is a normal turn end). - Epidemiology. Case definition, prevalence/incidence, demographics,
natural history →
epidemiology.json. - Biology & standard of care. Mechanism, biomarkers, approved
therapies, guidelines, unmet need →
biology_soc.json. - Regulatory & trials. Accepted endpoints, precedents, design
parameters, landmark trials, failures →
regulatory_trials.json. - Synthesis. No new research threads (single targeted gap-fills only).
Write
indication_dossier_report.mdandresearch_output.json, then markprogress.jsoncomplete.
After each of phases 2–5, write the waypoint, emit a ≤200-word summary of findings and open uncertainties, and continue directly.
Resuming
When workdir already contains waypoints: list which phases are complete
(file exists and is non-empty), show the meta summary, and ask which phase to
run. Never overwrite an existing waypoint without confirmation.
Output layout
<workdir>/waypoints/
├── progress.json # loop control, flipped last
├── meta.json # phase 1
├── epidemiology.json # phase 2
├── biology_soc.json # phase 3
├── regulatory_trials.json # phase 4
├── sources_evaluated.json # appended by every phase
├── research_output.json # phase 5, structured
└── indication_dossier_report.md # phase 5, the deliverable
Signals
- GitHub stars
- 1k
- Forks
- 117
- Last commit
- Sep 2026
Advanced
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indication-dossier-xuzhougeng- Source
- github.com/xuzhougeng/wisp-science