indication-dossier

name	indication-dossier
description	Generate a therapeutic indication dossier. Covers the patient population, epidemiology, disease biology, standard of care, regulatory precedent, and landmark clinical trials.
license	Apache-2.0
origin	openai4s
capabilities	{"network":{"mode":"none","domains":[]}}

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 call ask_user with options Proceed / Revise identity / Stop, so a misread indication name can be caught before the expensive phases run. If ask_user is unavailable, state "proceeding on this interpretation; interrupt now to correct it" and continue.

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.