---
name: Trial Readout Analysis
slug: trial-readout-analysis
category: AI Engineering
description: Trial Readout Analysis reviews clinical-trial readouts with AdCom-style scrutiny of endpoints, statistics, subgroups, missing data, safety, and benefit-risk. It also sizes likely stock reactions using historical analogues before and after a readout.
github: "https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/bio-pharm/skills/agentii/trial-readout-analysis"
language: Python
stars: 203
forks: 16
install: "npx degit https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/bio-pharm/skills/agentii/trial-readout-analysis ~/.claude/skills/trial-readout-analysis"
installs_to: ~/.claude/skills/trial-readout-analysis
source_path: plugins/vertical-plugins/bio-pharm/skills/agentii/trial-readout-analysis/SKILL.md
collection_size: 21
category_size: 3101
collection_url: "https://dirskills.com/collections/agentii-ai/agentii-investment-intelligence"
added: 2026-09-05T05:29:53.230Z
last_synced: 2026-09-05T05:29:53.230Z
canonical_url: "https://dirskills.com/skills/trial-readout-analysis"
---

# Trial Readout Analysis

Trial Readout Analysis reviews clinical-trial readouts with AdCom-style scrutiny of endpoints, statistics, subgroups, missing data, safety, and benefit-risk. It also sizes likely stock reactions using historical analogues before and after a readout.

**Install:**

```bash
npx degit https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/bio-pharm/skills/agentii/trial-readout-analysis ~/.claude/skills/trial-readout-analysis
```

## README

> Methodology inspired by publicly taught clinical-trial frameworks; all text is an original paraphrase.

## Defaults

| Parameter | Default Value | Rationale |
|-----------|---------------|-----------|
| scrutiny_axes | all six | Safety/stats/subgroups/missing data/endpoints/benefit-risk |
| outcome_framing | base/bull/bear | Binary readouts need scenario sizing |
| reaction_context | historical cases | Size moves from past analogues |

## Preflight

Run canonical pre-flight per `contracts/preflight.md`. Propagate X-Agentii-Trace per `contracts/x-agentii-trace-header.md`.

## Triggers

- "Evaluate [ticker]'s upcoming trial readout."
- "What should I look for in [trial]'s data?"
- "Size the readout for [drug] phase 3."
- "What did the AdCom-style scrutiny say about similar trials?"
- "Base/bull/bear for [ticker]'s readout."
- "Which endpoints matter for [trial]?"
- "How has the market reacted to similar readouts?"
- "Readout checklist for [ticker]."
- "Is this trial design adequate?"
- "What are the red flags in [trial]'s design?"

## Production Grounding

- Readout ≠ approval: phase-3 success is necessary but not sufficient; FDA re-analyzes sponsor data.
- Apply the six scrutiny axes (safety signals, statistical adequacy, subgroup analyses, missing data, endpoint appropriateness, benefit-risk) — the 道/法 frameworks in `references/knowledge-frameworks.md` are the authoritative checklist.
- Readout framing: readout design, then stock sizing (binary-risk expected value), then historical analogue comparison.

## Data Source Priority

1. `search_clinical_trials` / `get_clinical_trial` — design, status, endpoints, dates.
2. `search_documents` / `read_source_*` — sponsor disclosure, prior data cuts.
3. `search_fda_approvals` — regulatory history of the drug/program.
4. Knowledge layer: `search_investment_cases(event_type=trial_readout|adcom_vote)` + strategies for judgment frameworks.

## Methodology

### Retrieval Scope
unstructured_document_search

### Retrieval Strategy
1. Pull the trial record (`get_clinical_trial` by NCT id, or `search_clinical_trials` by drug/ticker).
2. Assess design + endpoint quality against scrutiny axes.
3. Frame base/bull/bear outcomes with sizing.
4. Ground in historical readout/adcom cases via knowledge tools.

### Temporal Scope
See frontmatter temporal_scope block.

### Tool Allowlist
See frontmatter allowed_tools.

### Protocol
1. Trial record
2. Scrutiny-axes assessment
3. Outcome scenarios + sizing
4. Analogue grounding

## Modes

- **Pre-readout** (default): design scrutiny + scenario sizing.
- **Post-readout**: results evaluation + reaction context.
- **Program view**: multiple trials across a program.

## Tool Fallbacks

| Failure | Fallback |
|---------|----------|
| search_clinical_trials empty | Use filings + press via `search_documents`; annotate coverage_gap |
| Trial record thin | Note undisclosed fields; do not fabricate |
| Knowledge tools empty | Proceed with structured data + static frameworks |

## Output File

`{ticker}/{YYYY-MM-DD_HHMM}_trial-readout-analysis_{affix}.md`

## Output Structure

1. **Executive Summary** — readout stance in 2-3 sentences
2. **Trial Profile** — design, endpoints, status, dates
3. **Scrutiny Assessment** — the six axes with evidence
4. **Outcome Scenarios** — base/bull/bear with sizing
5. **Historical Analogues** — cases with /v/ citations
6. **Coverage Gaps** — degraded flags

## Error Handling

| Error | Fallback |
|-------|----------|
| NCT id unknown | Search by drug/ticker; flag if unresolved |
| Endpoints undisclosed | Flag explicitly; scrutiny limited to disclosed data |

## Memory Load

See `contracts/memory-load.md`.

## Snapshot

See `contracts/snapshot-synthesis.md`.

## Final Summary (TUI)

Include ### Key Citations block with 0-10 clickable /v/ URLs.

## References

- `contracts/citation-and-memory.md`
- `contracts/output-frontmatter-schema.md`
- `contracts/memory-load.md`
- `contracts/snapshot-synthesis.md`
- `contracts/preflight.md`
- `references/knowledge-frameworks.md`