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-market-sizinggit 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-market-sizing)<a href="https://agentmods.dev/skills/agentii-ai/agentii-investment-intelligence/med-market-sizing"><img src="https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/med-market-sizing/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-market-sizing"><img src="https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/med-market-sizing.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 | $0.00070 | $0.01729 |
| Opus 5.5 | $0.00028 | $0.00692 |
| Sonnet 5.5 | $0.00014 | $0.00346 |
| Haiku 4.5 | $0.00007 | $0.00173 |
Grade A, and why
med-market-sizing 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 — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Methodology inspired by publicly taught patient-flow sizing approaches; all text is an original paraphrase.
Defaults
| Parameter | Default Value | Rationale |
|---|---|---|
| funnel_stages | 7 | prevalence → diagnosed → interested → affordable → covered → treated → persistent |
| affordability_rule | ~10% monthly budget | Income-share rule per cohort and country |
| scenario_grid | bull/base/bear | Never a single point number |
| analog_anchors | named | Statins for penetration, tech S-curves for adoption |
| capacity_state | explicit | Supply-constrained vs demand-limited + flip condition |
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 market queries.
Triggers
- "What is the TAM for [therapy area]?"
- "Size the market for [drug/device] in [indication]."
- "What has to be true for the bear case in [class]?"
- "Walk me through the patient funnel for [indication]."
- "Is [class] supply-constrained or demand-limited?"
- "What capacity ceiling do [company]'s plants impose?"
- "Anchor [class] adoption to a historical analog."
- "Bull/base/bear sizing for [indication] with drivers."
- "How does the income-share rule cap affordability?"
- "What penetration rate is realistic for [class]?"
- "How much API does [class] need per patient-year?"
Production Grounding
- Funnel: prevalence → diagnosed → interested → affordable (income-share rule, ~10% of monthly budget) → covered → treated → persistent; every stage carries an explicit rate or a
coverage_gap. Price as price × duration per cohort and country; never skip a stage silently. - Capacity check is mandatory: plants × units/yr, API kg/patient/yr, fill-finish lead times. State whether the market is supply-constrained or demand-limited and the condition that flips it.
- Analog anchoring: named historical analogs (statins for penetration, tech S-curves for adoption); every anchor carries its citation.
- Scenario discipline: bull/base/bear with a named-driver assumption grid; uncertainty at market level, POS at asset level; model-vs-consensus delta always explicit; abstain where unquantifiable.
- 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 5c75bc4490ef
- 1mo ago First seen · 160 lines · 70 tokens per session scan A c91e69fdda65
med-market-sizing is a skill published in the GitHub repository agentii-ai/agentii-investment-intelligence (208 stars, last pushed yesterday), licensed Apache-2.0. It adds 70 tokens to every session and 1,729 once invoked, about $0.0003 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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