Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add agentii-ai/agentii-investment-intelligence --skill trial-readout-analysisgit clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligenceWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/agentii-ai/agentii-investment-intelligence/trial-readout-analysis)<a href="https://agentmods.dev/skills/agentii-ai/agentii-investment-intelligence/trial-readout-analysis"><img src="https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/trial-readout-analysis/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/agentii-ai/agentii-investment-intelligence/trial-readout-analysis"><img src="https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/trial-readout-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00056 | $0.01230 |
| Opus 5 | $0.00028 | $0.00615 |
| Sonnet 5 | $0.00011 | $0.00246 |
| Haiku 4.5 | $0.00006 | $0.00123 |
Grade A, and why
trial-readout-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.mdare the authoritative checklist. - Readout framing: readout design, then stock sizing (binary-risk expected value), then historical analogue comparison.
Data Source Priority
search_clinical_trials/get_clinical_trial— design, status, endpoints, dates.search_documents/read_source_*— sponsor disclosure, prior data cuts.search_fda_approvals— regulatory history of the drug/program.- Knowledge layer:
search_investment_cases(event_type=trial_readout|adcom_vote)+ strategies for judgment frameworks.
Methodology
Retrieval Scope
unstructured_document_search
Retrieval Strategy
- Pull the trial record (
get_clinical_trialby NCT id, orsearch_clinical_trialsby drug/ticker). - Assess design + endpoint quality against scrutiny axes.
- Frame base/bull/bear outcomes with sizing.
- Ground in historical readout/adcom cases via knowledge tools.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago Changed · +1 lines 47dd82675774
- 7d ago First seen · 147 lines · 56 tokens per session scan A 019a0805f4b6
trial-readout-analysis is a skill published in the GitHub repository agentii-ai/agentii-investment-intelligence (204 stars, last pushed 2d ago), licensed Apache-2.0. It adds 56 tokens to every session and 1,230 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
Other skills, from other repositories
event-study-cars
Complete methodology for computing publication-quality cumulative abnormal returns with proper event-study test statistics, matching the robustness of Kaspereit's eventstudy2 for Stata. Covers dateline construction, event-date mapping, estimation and event windows, thin-trading adjustment, OLS with Theil prediction…
chanlun-engine-skill
A Chinese-language stock-analysis skill based on Chan theory, a method for interpreting price-chart structures such as turning points and trading ranges.
review-dose-optimisation-cost-access
Reviews Dose optimisation for cost and access evidence pack for the L3 task «Dose optimisation for cost and access». Produces a source-linked finding register with denominators and an explicit refuse list. Use when a practitioner asks to work this topic — e.g. "Please review the materials for Dose optimisation for…
funding-allocation
Analyze university and research institution funding allocation systems including RCM revenue attribution, performance-based budgeting, faculty startup package management, F&A indirect cost recovery distribution, equipment sharing and core facility recharge rates.
deal-packet
Produce the full institutional deal packet for a deal — Excel underwriting model + Word IC memo + PowerPoint deck + PDF one-pager — all Bristol-branded, fully cited, and cross-linked to one sources registry. Use when the user says "build the packet," "full workup," "put together the IC package," "model this deal," or…
deal-memo
Assemble research into a polished investment committee memo, market study, or deal one-pager. Use when the user says "write the memo," "put together an IC memo," "make a one-pager," "turn this into a document for the committee/lenders/LPs," or wants research packaged into a deliverable.