Borrowing it
Nothing to install: this file belongs to BlueWaterCorp/RiskModels_API. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/BlueWaterCorp/RiskModels_API/main/.agents/skills/riskmodels-smart-subheader/SKILL.mdgit clone --depth 1 https://github.com/BlueWaterCorp/RiskModels_APIWrote 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/bluewatercorp/riskmodels_api/riskmodels-smart-subheader)<a href="https://agentmods.dev/skills/bluewatercorp/riskmodels_api/riskmodels-smart-subheader"><img src="https://agentmods.dev/badge/skills/bluewatercorp/riskmodels_api/riskmodels-smart-subheader/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/bluewatercorp/riskmodels_api/riskmodels-smart-subheader"><img src="https://agentmods.dev/badge/skills/bluewatercorp/riskmodels_api/riskmodels-smart-subheader.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 | $0.00048 | $0.00781 |
| Opus 5.5 | $0.00019 | $0.00312 |
| Sonnet 5.5 | $0.00010 | $0.00156 |
| Haiku 4.5 | $0.00005 | $0.00078 |
Grade A, and why
riskmodels-smart-subheader 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 2mo 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RiskModels Smart Subheader Generator
When building or refining any chart in sdk/riskmodels/snapshots/ or sdk/riskmodels/visuals/
(R1 profile, waterfall, hedge cascade, etc.), generate the subheader (the italic explanatory
sentence(s) under each section title) using the smart_subheader module.
Module Location
sdk/riskmodels/visuals/smart_subheader.py
Usage
from riskmodels.visuals.smart_subheader import generate_subheader
text = generate_subheader(
chart_type="er_attribution", # or "hr_cascade", "peer_table", etc.
title="L3 Explained-Return Attribution",
data=metrics_dict, # the raw metrics powering the chart
data_as_of="2026-04-04", # from RiskLineage.data_as_of
time_range="past 252 trading days",
ticker="NVDA",
benchmark="SOXX",
use_llm=False, # True to enable LLM enhancement
)
Supported Chart Types
| chart_type | Used by | Description |
|---|---|---|
er_attribution |
R1 Panel I | L3 ER decomposition horizontal bar |
hr_cascade |
R1 Panel II | Hedge-ratio cascade grouped bar |
peer_table |
R1 Panel III | Peer comparison table |
waterfall |
S2, future R3 | Return attribution waterfall |
histogram |
Future R2/P2 | Cross-sectional distribution |
multi_line |
Future R2/P2 | Time series overlay |
stacked_area |
Future R4 | Factor contribution stacked area |
Strict Rules
- Always mention the exact time range (e.g. "over the past 252 trading days ending 2026-04-04")
- Always include data_as_of from lineage
- Use only real numbers from the data dict — never round, estimate, or hallucinate
- Never say "outperformance by X%" without the exact period
- Max 2 short sentences, institutional tone (think Bloomberg PORT commentary)
- Rule-based mode is the default — no LLM dependency for rendering
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.
- 2mo ago First seen · 91 lines · 48 tokens per session scan A a7560bfcebbc
riskmodels-smart-subheader is a skill published in the GitHub repository BlueWaterCorp/RiskModels_API (0 stars, last pushed yesterday), licensed Apache-2.0. It adds 48 tokens to every session and 781 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 2026-08-31.
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