Omega Point ships a growing catalog of AI Agent Skills you can run inside any compatible agent interface — Claude Code, the Claude API / Agent SDK, or a third-party agent framework that supports the open Anthropic Agent Skills format. Every skill is delivered as a single self-contained .zip file from your Solutions tab.

This article walks you through:

The download process is the same for every skill — and the same regardless of which AI agent you eventually load it into.

Every .zip contains an EXPORT_INFO.txt manifest at its root, listing the skill name, plugin, version, git ref, commit SHA, and export timestamp. Compare the version against the one listed next to each skill in the catalog below to confirm you have the build documented here.

Most skills in this catalog need an Omega Point API key (also called an API token) to talk to the OP GraphQL API on your behalf. You generate and manage keys from the same Omega Point platform — no separate portal.

No keys listed? If you do not see any keys, click the + button at the top of the list to create a new one, or reach out to [email protected] if you need help with permissions.

The skills below appear on your Solutions tab in the same categories and order. Each entry lists the version shipped in the current release, the canonical plugin/skill identifier, the exact filename to expect after download, and what the skill does.

op-cx/portfolio-upload · File: portfolio-upload-0.4.1.zip

End-to-end workflow for uploading a holdings or positions file into Omega Point. The skill validates security coverage, helps resolve unmapped securities with proxies (SEDOL / FIGI / custom mappings), and runs post-upload data quality checks — flagging performance spikes, GMV jumps, and unexpected net exposure shifts before the portfolio is used downstream.

Use when: Loading a new portfolio or refreshing daily positions; validating coverage after an upload; investigating data quality issues.

op-cx/permissions-management · File: permissions-management-0.4.1.zip

Grant, modify, list, or revoke permissions on Omega Point resources — portfolios, baskets, watchlists, and forecasts — for individual users and teams via the OP GraphQL API. Supports bulk operations (e.g. permission a set of portfolios for a new analyst) and access audits (who can see or edit a given resource). Requires an account-admin token.

Use when: Sharing a portfolio with a colleague, onboarding a new analyst, restricting access to a sensitive basket, or auditing who has visibility into a given resource.

op-cx/op-api-training-examples · File: op-api-training-examples-0.4.1.zip

A reference library of Omega Point GraphQL API patterns covering the full data lifecycle: ingestion (portfolios, baskets, forecasts, classifications, content sets), optimization workflows (basic, active vs benchmark, forecast-driven, implied-returns reweight), analysis queries (performance, risk, exposure, composition), and clean-up operations such as deleting position-set or basket dates. Use it as the source-of-truth when writing Python against the OP API or debugging existing integrations.

Use when: Building or debugging any Python integration against the OP GraphQL API; looking up the correct mutation or query pattern for an OP data workflow.

op-investor/factor-hedge-finder · File: factor-hedge-finder-0.13.0.zip

Find clean composite securities — indexes, baskets, or both — to hedge a specific factor exposure in a portfolio or a single name. The skill screens for high-factor-exposure instruments while minimizing unintended side exposures, and recommends what to short or long for a tight, low-noise hedge against named risk-model factors (Beta, Momentum, Growth, Residual Vol, etc.).

Use when: Reducing exposure to a specific factor without disturbing the rest of the portfolio; selecting an index or ETF to short as a clean factor hedge.

op-investor/factor-event-study-api-only · File: factor-event-study-api-only-0.13.0.zip

Build a factor event study using Omega Point factor return data — analyze how risk-model factors behave around a specific macro event, trigger, or market signal. Stress-tests a portfolio against historical factor shocks, overlays portfolio (and optionally benchmark-relative) exposures on factor returns, and produces a self-contained interactive React artifact you can share.

Use when: Asking "how would my portfolio have behaved during the last X-style shock?"; analyzing factor behavior around macro events; quantifying tail sensitivity to a given factor regime.

op-investor/earned-vs-bought · File: earned-vs-bought-0.13.0.zip

Lead/lag analysis of trades versus factor-exposure changes. Determines whether portfolio alpha is earned through proactive positioning ahead of factor moves, or bought by chasing factor moves after the fact. Reconstructs trades from mark-to-market math, computes Pearson correlations across configurable lag windows, and classifies each security (and the portfolio as a whole). Runs Momentum, Beta, and Residual Volatility by default; supports single-manager and multi-manager modes — the latter segments by a position-level attribute (e.g. Fund Tag) and aggregates per manager with click-to-drill.

Use when: Asking "are my trades leading or lagging momentum?"; diagnosing PM skill across factor regimes; segmenting a multi-PM book by who is proactive vs reactive.

op-investor/bias-stat-dashboard · File: bias-stat-dashboard-0.13.0.zip

Interactive HTML dashboard for risk-model evaluation. Compare multiple risk models — Barra, Axioma, Wolfe — on bias statistic, factor bias, idio bias, rolling bias, and coverage, to determine which models best fit a given portfolio. Useful before committing to a model for production risk reporting or optimization.

Use when: Choosing a primary risk model for a strategy; periodically validating that an existing model still fits the portfolio's behaviour.

op-investor/historical-portfolio-multi-model · File: historical-portfolio-multi-model-0.13.0.zip

Comprehensive multi-model historical analysis of a single portfolio across two or more Omega Point risk models. Covers six dimensions side-by-side: performance attribution, risk decomposition, exposure differences, drawdown anatomy, forward-looking factor signals, and lead/lag (Earned vs Bought) exposure timing. Produces an interactive HTML dashboard plus an executive-summary Word document.

Use when: Comparing variants of the same model provider or across model providers on the same portfolio; building a board-ready summary of model-choice impact.

op-investor/theme-basket-generator · File: theme-basket-generator-0.13.0.zip

Generate Noonum knowledge-graph powered thematic baskets. Start from top macro / financial news themes, or supply a custom theme objective (e.g. "Strait of Hormuz exposure", "AI infrastructure capex"), and the skill builds beneficiaries and laggards baskets ready to load into Omega Point for exposure analysis, hedging, or trading.

Use when: Operationalizing a thematic view; building long/short baskets around a news-driven theme.

Additional requirement: this skill needs a Noonum API key in addition to your Omega Point key. Check your Solutions tab for a card titled "Your specific skills, keys, and outputs" — your Noonum key will be there if your account has been provisioned with one. If you don't see it, contact your Omega Point customer support team at [email protected] to request one.

op-investor/thematic-package-analytics · File: thematic-package-analytics-0.13.0.zip

Portfolio thematic performance attribution against the Omega Point Thematic Package — daily β-z-weighted decomposition of returns onto ~600 themes, with multiplicative cumulative attribution, cumulative theme factor returns, annualized realized vol, and TFR R² per theme. Includes a Theme Universe / Theme Monitor view for universe-wide cumulative TFR and TSI snapshots. Output is a single self-contained interactive HTML dashboard with two tabs.

Use when: Asking "which themes drove my portfolio's return last quarter?"; monitoring how every theme is behaving this month; running thematic attribution against Axioma or Barra (idio or total return).

op-investor/historical-beta · File: historical-beta-0.13.0.zip

Compute historical betas, t-stats, and sensitivities for any universe of securities against any list of themes (composites — ETFs, custom baskets, factor proxies). Optionally produces a self-contained interactive HTML beta explorer with search and screener tabs.

Use when: Screening a watchlist by β to a theme; regenerating a historical-beta table for a risk model; building a beta explorer to share with PMs.

If a skill does not appear on your Solutions tab, if a download fails, or if your AI agent does not recognize an installed skill, contact your Omega Point representative — or write to [email protected] or [email protected]. Please mention which agent interface you are using so we can route the question correctly.