Indication dossier
Open-source, local-first desktop AI research workbench for scientific computing with Python/R, MCP bioinformatics tools, SSH/WSL/GPU runtimes, and OpenAI/Anthropic models.
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What its author says it does
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Generate a therapeutic indication dossier. Covers the patient population, epidemiology, disease biology, standard of care, regulatory precedent, and landmark clinical trials.
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SKILL.md
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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.