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 med-event-takeawaysgit 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/med-event-takeaways)<a href="https://agentmods.dev/skills/agentii-ai/agentii-investment-intelligence/med-event-takeaways"><img src="https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/med-event-takeaways/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/med-event-takeaways"><img src="https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/med-event-takeaways.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00090 | $0.01719 |
| Opus 5.5 | $0.00036 | $0.00688 |
| Sonnet 5.5 | $0.00018 | $0.00344 |
| Haiku 4.5 | $0.00009 | $0.00172 |
Grade A, and why
med-event-takeaways 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 1mo 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 — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Methodology inspired by publicly taught sell-side note-writing practice; all text is an original paraphrase.
Defaults
| Parameter | Default Value | Rationale |
|---|---|---|
| note_anatomy | 9 sections | headline → per-stock → KOL → lattices → deltas → vectors → risks → trackers |
| delta_framing | peak × POS | Modeled deltas vs consensus are unadjusted peak × POS |
| conflict_policy | materiality-rated | Surface verbatim, rate materiality, or defer to an outcomes trial |
| vector_set | estimates/thesis/positioning | The three what's-changed vectors per covered name |
Preflight
Run canonical pre-flight per contracts/preflight.md. Include the X-Agentii-Trace header on every tool call per contracts/x-agentii-trace-header.md — carry the _run_id from your first tool result and name yourself (and your parent, if you were spawned). Confirm ticker resolution via search_companies before event queries.
Triggers
- "Write the note on [conference / KOL event]."
- "What are the takeaways from [event] for my coverage?"
- "Distill the [conference] KOL panel on [drug/class]."
- "What changed for [ticker] after [event]?"
- "Model the delta to consensus from [event]'s data."
- "Which stocks move on [event] and why?"
- "Conflict check: what did KOLs disagree on at [event]?"
- "What do I update first — estimates, thesis, or positioning?"
- "Summarize the cross-trial comparisons from [event]."
- "Upside and downside risks after [event]."
- "Link the living trackers that [event] should update."
Production Grounding
- Note anatomy is fixed: headline verdict (paragraph one) → per-stock takeaways with model numbers → KOL distillation → raw data + cross-trial lattices → modeled deltas vs consensus (unadjusted peak × POS) → three what's-changed vectors (estimates / thesis / positioning) → risk bullets → living-tracker links.
- Conflict rule: conflicting views surfaced verbatim, rated by materiality ("incremental positive, not narrative-changing") or deferred to a larger outcomes trial — never silently averaged.
- Consensus delta: model-vs-consensus always explicit; POS changes logged with reasons; abstain where unquantifiable.
- Buy-side lens: client-question section, where investor attention sits, per-name bull/bear pivot conditions.
- Badges:
[FACT]/[DEDUCTED]/[VIEW]with the summary table.
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.
- 1mo ago Changed · +1 lines 3e72f183654b
- 1mo ago First seen · 158 lines · 90 tokens per session scan A a64433eec01a
med-event-takeaways is a skill published in the GitHub repository agentii-ai/agentii-investment-intelligence (208 stars, last pushed yesterday), licensed Apache-2.0. It adds 90 tokens to every session and 1,719 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-09-15.
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