Skill
Trial evidence trace
Paste one clinical-trial ID; get the exact published papers that describe it — pulled from Amass's publication↔trial graph, with trust metadata and abstract-grounded relevance notes.
New to Amass? Connect Amass to Claude first
The prompt
Paste this into Claude
NCT04611802Use the Trial evidence trace skill.
Clinical-trial ID (NCT or AMTC): NCT04611802Why not just ask the model?
Ask a plain model "which papers describe NCT04611802?" and it invents plausible citations and PMIDs, because it has no real trial→paper map to read from.
- Plain model: fabricates titles, PMIDs, and journals that "sound like" the trial's literature, and conflates papers that merely cite COVID-vaccine work with the ones that actually report this trial.
- Amass: the trial record carries a first-class
referencesBiomedCoreedge — the Amass IDs of the publications that describe it. Each fetched paper returns its verbatim title, journal,publicationDate,citationCount,journalQualityJufo, andisRetracted, with a relevance note quoted straight from the returned abstract. Nothing is guessed.
Why a skill, not a prompt?
This is a multi-step orchestration, not a one-shot lookup: one get_amass_trialcore_record reads the trial's referencesBiomedCore array, then a get_amass_biomedcore_record by-id fan-out runs once per referenced paper to pull its trust metadata and abstract, then a templated roll-up sorts by citation count and emits the CSV. Packaging it as a skill means the rate-limit-batched fan-out — and the metadata-only recovery for trials whose landmark papers overflow the per-call token budget — ships once and triggers with a single line, instead of re-pasting a brittle procedure every time.
Honest scope
The describing-paper count is the trial's referencesBiomedCore length (7 for PREVENT-19), not an exhaustive literature search — broaden coverage by also searching BioMedCore for the trial's acronym and unioning the results. Citation counts and trust metadata are verbatim from Amass and can lag the source databases by hours. Every relevance note is grounded in the paper's own abstract; where the abstract is silent it reads "not in abstract", and no trial-outcome string is paraphrased from a field the MCP does not expose (it does not surface primaryOutcomeMeasures).
Install the skill
Add the skill to Claude
Install every Amass skill with one command — npx skills add amass-technologies/public-skills — or download the SKILL.md from GitHub and add it to Claude (Settings → Capabilities → Skills, or drop it in your Claude Code skills directory). Then paste the prompt above to trigger it.
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Name a drug, target, mechanism, or indication; get a landscape briefing that maps the published literature AND the clinical pipeline together — every paper and trial carrying a real Amass ID, PMID, or NCT you can check.
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AMASS EVIDENCE BRIEF
Tirzepatide evidence brief
Name a drug asset; get a citation-auditable Word evidence brief — pivotal Phase-3 trials, grounded efficacy and safety findings, and the trial↔paper links — every figure verbatim from Amass.
Run it yourself
Connect Amass to Claude and paste the prompt.
No build, no deploy — the connector takes about a minute, then this workflow runs on your own inputs.