Clinical-trial readout analysis: pull the trial, evaluate the readout with AdCom-style scrutiny (endpoints, statistics, subgroups, missing data, safety), and size the stock reaction with historical grounding. The judgment core for binary biotech events.
Scanned 9/7/2026
Install to Claude Code
npx -y skills add agentii-ai/agentii-investment-intelligence --skill trial-readout-analysis --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Trial Readout Analysis?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/agentii-ai-trial-readout-analysis)More formats (shields.io, HTML) on the badges page.
---
name: trial-readout-analysis
description: "Clinical-trial readout analysis: pull the trial, evaluate the readout with AdCom-style scrutiny (endpoints, statistics, subgroups, missing data, safety), and size the stock reaction with historical grounding. The judgment core for binary biotech events."
multi_ticker_semantics: single_target
temporal_scope:
default_quarters: 4
max_quarters: 8
description: "Readout window default 4 quarters; up to 8 for multi-trial programs."
allowed_tools:
- search_clinical_trials
- get_clinical_trial
- search_documents
- search_sec_filings
- read_source_outline
- read_source_pages
- get_company_profile
- search_fda_approvals
- search_investment_cases
- get_investment_case
- search_investment_strategies
- get_investment_strategy
- search_by_analogue
- search_knowledge_entries
- get_knowledge_entry
retrieval_scope: unstructured_document_search
min_tool_diversity: 3
parameter_free: false
---
> 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`
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!