Indication dossier
Generate a therapeutic indication dossier. Covers the patient population, epidemiology, disease biology, standard of care, regulatory precedent, and landmark clinical trials.From its SKILL.md
npx -y skills add xuzhougeng/wisp-science --skill indication-dossierAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- fetches URLsInstructs the agent to fetch 2 URLs, including clinicaltrials.gov and 1 more.
What its file declares
Copied from the file, not written here
The file declares its own license as Apache-2.0. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
5.7 KB, ~1.3k tokens by cl100k_base, as published. Nobody here has run it
Indication Dossier
Produces a structured research dossier on a single indication, framed as a patient population: who they are, what's wrong, how they're treated today, and how clinical trials can be designed to help them. Runs as five phases that write resumable waypoint files; after a brief identity check at the end of Phase 1, the remaining phases run straight through.
Framing
Think of an indication as a patient population. Frame everything from the patient perspective: "Who are these patients?" not "What is this disease?"; "How are these patients identified and managed?" not "What causes this condition?"; population nesting: "all patients in {child} are patients in {parent}".
Some indications don't map to ICD codes or standard disease definitions: "immunosenescence" is a biological state, not a billable diagnosis; "ageing" is not an FDA-accepted indication; "GLP-1 induced sarcopenia" is an iatrogenic population. Note these distinctions explicitly. They matter for regulatory path and trial design.
Inputs
indication(required) — indication name (e.g., "sarcopenia", "idiopathic pulmonary fibrosis").additional_context(optional) — areas to focus on, parent indication, or other framing.workdir(optional) — where to write waypoints and the final report. Defaults to./do_not_commit/indication-dossier-<slug>/.
Tools this skill expects
| Purpose | Tool |
|---|---|
| ClinicalTrials.gov | clinical-trials MCP |
| Literature | pubmed MCP |
| Web | WebSearch, WebFetch — FDA guidance, treatment guidelines (NCCN, AASLD, specialty societies), CDC/WHO epidemiology data |
| Documents | WebFetch for remote PDFs; Read for local PDFs |
| Subagents | Agent for parallel evidence gathering |
If a listed MCP isn't connected, say so and fall back to WebSearch against
the underlying public source (clinicaltrials.gov, pubmed.ncbi.nlm.nih.gov).
Output layout
<workdir>/
└── waypoints/
├── progress.json # loop control
├── meta.json # phase 1
├── epidemiology.json # phase 2
├── biology_soc.json # phase 3
├── regulatory_trials.json # phase 4
├── sources_evaluated.json
├── research_output.json # phase 5 — structured output
└── indication_dossier_report.md # phase 5 — the deliverable
Schemas for every waypoint file are in references/waypoint-schemas.md.
Waypoints are the resumable state. If the workdir already has waypoints, read
them, summarize what's done, and ask which phase to resume from.
Before starting
Read references/00-research-standards.md. It governs sourcing and the
anti-fabrication rules for every phase. Then create <workdir>/waypoints/.
Workflow
The dossier is built in five phases. After each phase, write the waypoint
file and emit a ≤200-word summary of what you found and what's uncertain,
then proceed directly to the next phase. The one exception is Phase 1: after
writing meta.json, show the resolved indication identity and end the turn
with a concise request for Proceed, Revise identity, or Stop. Do
not start the expensive phases until the user answers; Wisp has no separate
interactive-question tool that can be called from the workflow.
Phase 1 — Meta initialization
Read references/01-meta-initialization.md. Resolve the indication identity:
clinical definition, ICD codes, aliases, parent indication, and whether it's
a recognized diagnostic entity. Run a quick CT.gov landscape scan. Stand up
waypoints/meta.json.
Phase 2 — Epidemiology research
Read references/02-epidemiology-research.md. Characterize the population:
diagnostic criteria, prevalence and incidence, demographics and risk factors,
natural history. Use parallel subagents to search PubMed and the web
simultaneously. Write waypoints/epidemiology.json.
Phase 3 — Biology & standard-of-care research
Read references/03-biology-soc-research.md. Establish pathophysiology,
biomarkers, approved therapies, treatment guidelines, and unmet need. Use
parallel subagents: PubMed for biology, web for guidelines, FDA for
approvals. Write waypoints/biology_soc.json.
Phase 4 — Regulatory & trials research
Read references/04-regulatory-trials-research.md. Establish FDA/EMA
accepted endpoints, regulatory precedents, typical trial design parameters,
landmark trials, and notable failures. Use parallel subagents: FDA for
guidance/approvals, CT.gov for trial patterns, PubMed for trial-history
reviews. Write waypoints/regulatory_trials.json.
Phase 5 — Synthesis
Read references/05-synthesis.md and references/06-writing-style.md. Read
all four consolidated waypoint files. Write
waypoints/indication_dossier_report.md — narrative sections in the order
the synthesis reference specifies, with inline citations per the style guide
— and waypoints/research_output.json. No new research threads in this
phase. Targeted gap-fills are allowed: a single fetch to resolve a specific
missing value in an existing waypoint field (an approval year, an NCT ID, a
figure from a sponsor pipeline page). Anything broader than that, name as a
gap rather than filling it.
Resuming
If invoked with a workdir that already contains waypoints: list which phases
are complete (waypoint file exists and is non-empty), show the meta summary,
and ask the user which phase to run next. Never overwrite an existing waypoint
without confirmation.
What ships with it: 8 files
21.9 KB alongside SKILL.md
references/
- 00-research-standards.md3.0 KB
- 01-meta-initialization.md1.7 KB
- 02-epidemiology-research.md2.1 KB
- 03-biology-soc-research.md2.3 KB
- 04-regulatory-trials-research.md3.1 KB
- 05-synthesis.md5.2 KB
- 06-writing-style.md1.7 KB
- waypoint-schemas.md2.9 KB
Gives 0 of the 12 instructions most healthcare skills give in ~1.3k tokens
Counted across 147 of the 152 authors here whose files we hold, read 2026-08-07
- Export trial data to CSV formatin 11 of 147, across 2 files
- Retrieve trial details using an NCT IDin 11 of 147, across 2 files
- Split clinical datasets strictly by patientin 11 of 147, across 3 files
- Use the ClinicalTrials.gov API v2in 10 of 147, across 1 file
- Search trials by condition, drug, location, status or phasein 10 of 147, across 1 file
- Use maximum page size for bulk data retrievalin 10 of 147, across 1 file
- Extract and summarize key study informationin 10 of 147, across 1 file
- Combine multiple filters for targeted searchesin 10 of 147, across 1 file
- Print and review dataset statistics before modelingin 8 of 147, across 1 file
- Start model development with simple baselinesin 8 of 147, across 1 file
- Match preprocessing processors directly to data typesin 8 of 147, across 1 file
- Monitor validation metrics for task type and class imbalancein 8 of 147, across 1 file
Said here and by no other author read
- frame everything from patient perspective
- note nonstandard indication distinctions explicitly
- read research standards before starting
- write waypoint file after each phase
- emit short summary after each phase
- halt after phase one for user confirmation
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.