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 mphinance/alpha-skills --skill exposure-coachgit clone --depth 1 https://github.com/mphinance/alpha-skillsWrote 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/mphinance/alpha-skills/exposure-coach)<a href="https://agentmods.dev/skills/mphinance/alpha-skills/exposure-coach"><img src="https://agentmods.dev/badge/skills/mphinance/alpha-skills/exposure-coach/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/mphinance/alpha-skills/exposure-coach"><img src="https://agentmods.dev/badge/skills/mphinance/alpha-skills/exposure-coach.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 | $0.00050 | $0.01355 |
| Opus 5.5 | $0.00020 | $0.00542 |
| Sonnet 5.5 | $0.00010 | $0.00271 |
| Haiku 4.5 | $0.00005 | $0.00136 |
Grade A, and why
exposure-coach 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Exposure Coach
Overview
Exposure Coach synthesizes outputs from market-breadth-analyzer, uptrend-analyzer, macro-regime-detector, market-top-detector, ftd-detector, theme-detector, sector-analyst, and institutional-flow-tracker into a unified control-plane decision. The skill answers the solo trader's core question: "How much capital should I commit to equities right now?" before any individual stock analysis begins.
When to Use
- Before initiating any new stock positions to determine appropriate capital commitment
- At the start of each trading week to calibrate portfolio exposure
- When multiple market signals conflict and a unified posture is needed
- After significant macro or market events to reassess exposure ceiling
- When transitioning between market regimes (broadening, concentration, contraction)
Prerequisites
- Python 3.9+
- FMP API key (set
FMP_API_KEYenvironment variable) for institutional-flow-tracker data - Input JSON files from upstream skills (see Workflow Step 1)
- Standard library +
argparse,json,datetime
Workflow
Step 1: Gather Upstream Skill Outputs
Collect the most recent JSON outputs from integrated skills. Each file provides a specific signal dimension:
| Skill | Output File Pattern | Signal Provided |
|---|---|---|
| market-breadth-analyzer | breadth_*.json |
Advance/decline ratios, new highs/lows |
| uptrend-analyzer | uptrend_*.json |
Uptrend participation percentage |
| macro-regime-detector | regime_*.json |
Current regime (Concentration, Broadening, etc.) |
| market-top-detector | top_risk_*.json |
Distribution day count, top probability score |
| ftd-detector | ftd_*.json |
Failure-to-deliver anomalies |
| theme-detector | theme_*.json |
Active investment themes and rotation |
| sector-analyst | sector_*.json |
Sector performance rankings |
| institutional-flow-tracker | institutional_*.json |
Net institutional buying/selling |
Step 2: Run Exposure Scoring Engine
What ships with it
6 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 First seen · 152 lines · 50 tokens per session scan A de5dcc1bad1b
exposure-coach is a skill published in the GitHub repository mphinance/alpha-skills (28 stars, last pushed 10d ago), licensed MIT. It adds 50 tokens to every session and 1,355 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 2026-09-14.
Other skills, from other repositories
sector-rotation
An analysis framework for comparing industries in the Chinese A-share stock market, using business conditions, price momentum, valuation, and money flows. It produces rankings and higher- or lower-allocation suggestions.
strategy-pivot-designer
Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.
twitter-reader
Read Twitter/X for financial research through opencli: the user's home timeline, tweet search, trending topics, bookmarks, a user's recent tweets, threads, articles, profiles, followers and following, and notifications. Use this skill whenever the user wants to know what people are saying on Twitter/X or fintwit about…
energy-procurement
Codified expertise for electricity and gas procurement, tariff optimization, demand charge management, renewable PPA evaluation, and multi-facility energy cost management. Informed by energy procurement managers with 15+ years experience at large commercial and industrial consumers. Includes market structure analysis…
airdrop-hunting-guide
Guide to finding and qualifying for crypto airdrops — eligibility criteria, farming strategies, on-chain activity requirements, Sybil detection avoidance, and tracking tools. Use when helping users understand airdrops, check eligibility, or plan participation strategies.
china-portfolio-monitoring
A monitoring framework for tracking the financial results, operating measures, strategic milestones, and risks of companies held by China-focused private-equity funds. It uses measures such as revenue growth, margins, debt, cash flow, and return on equity.