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 pipeline-medicinesgit 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/pipeline-medicines)<a href="https://agentmods.dev/skills/agentii-ai/agentii-investment-intelligence/pipeline-medicines"><img src="https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/pipeline-medicines/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/pipeline-medicines"><img src="https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/pipeline-medicines.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 | $0.00060 | $0.01654 |
| Opus 5.5 | $0.00024 | $0.00662 |
| Sonnet 5.5 | $0.00012 | $0.00331 |
| Haiku 4.5 | $0.00006 | $0.00165 |
Grade A, and why
pipeline-medicines 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 — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Methodology inspired by publicly taught pipeline-valuation frameworks; all text is an original paraphrase.
Defaults
| Parameter | Default Value | Rationale |
|---|---|---|
| asset_scope | all disclosed assets | Full-pipeline enumeration first |
| pos_source | published phase transition ranges | Starting point, then adjusted with logged reasons |
| status_diff | true | Previous vs current trial status shown per asset |
| competitor_map | true | Same-target and same-indication crowding surfaced |
| value_frame | risk-adjusted | Modeled value = unadjusted peak x POS, both shown |
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 asset queries.
Triggers
- "Analyze [ticker]'s drug pipeline by phase."
- "What are the Phase II and III assets for [ticker]?"
- "Risk-adjust [ticker]'s pipeline with explicit POS assumptions."
- "Which of [ticker]'s programs is most valuable?"
- "What trials recently changed status for [ticker]?"
- "Who else is targeting [mechanism/target]?"
- "How crowded is [indication], and what does that mean for [ticker]?"
- "Log every POS change with reasons for [ticker]'s pipeline."
- "What is the next catalyst for each of [ticker]'s assets?"
- "Compare [ticker]'s pipeline against same-indication competitors."
- "Map [ticker]'s assets by mechanism of action."
- "What does [ticker]'s pipeline say about its runway?"
Production Grounding
- POS discipline: every asset carries an unadjusted peak sales estimate and a phase-appropriate POS; the modeled number is peak x POS, never a bare risk-adjusted figure. Every POS change is logged with its reason (trial data, competitor data, discontinuation) — silent POS drift is a defect.
- Phase ladder: Phase I safety/dosing, Phase II efficacy signal, Phase III registrational; option value rises with phase. Apply scrutiny axes when sizing pivotal assets.
- Status-diff discipline: show previous vs current status per trial (New/Suspended/Terminated/Ahead/Delayed/...); Terminated plus enrollment collapse is a red flag; recruitment-complete starts the readout clock.
- Competitor mapping: same-target and same-indication crowding discounts peak sales, not just POS; mechanism overlap explains class risk.
- Grounding detail lives in
references/knowledge-frameworks.md.
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 1a4832548a55
- 1mo ago First seen · 158 lines · 60 tokens per session scan A 5aa4609d5e1f
pipeline-medicines is a skill published in the GitHub repository agentii-ai/agentii-investment-intelligence (208 stars, last pushed yesterday), licensed Apache-2.0. It adds 60 tokens to every session and 1,654 once invoked, about $0.0002 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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