Provides three production-ready ML training examples (sentiment classification, text generation, RedAI trade classifier) with complete training scripts, deployment configs, and datasets. Use when user needs example projects, reference implementations, starter templates, or wants to see working code for sentiment analysis, text generation, or financial trade classification.

Tests marketplace visibility configurations and catalog tiers (preview catalog only)

Analyze mock data and examples for cultural assumptions, understanding what they communicate about who the product is for. Use when reviewing test data, documentation, or seed data.

A skill for generating Excalidraw-format diagrams from natural language descriptions. This skill helps create visual representations of processes, systems, relationships, and ideas without manual draw

Generate architecture diagrams as .excalidraw files from codebase analysis. Use when the user asks to create architecture diagrams, system diagrams, visualize codebase structure, or generate excalidraw files.

Use when working with *.excalidraw or *.excalidraw.json files, user mentions diagrams/flowcharts, or requests architecture visualization - delegates all Excalidraw operations to subagents to prevent context exhaustion from verbose JSON (single files: 4k-22k tokens, can exceed read limits)

Analyze unknown or inherited Excel files to understand what they do, document their purpose, audit formulas for errors, and assess maintainability risk. Use when: (1) User uploads an Excel file asking 'what does this do?', (2) User needs to understand an inherited/legacy spreadsheet, (3) User wants formula auditing or error detection, (4) User asks about spreadsheet risk, complexity, or documentation, (5) User mentions 'inherited', 'legacy', 'undocumented', or 'someone left' regarding Excel files.

When the user has an Excel file with incomplete data that needs to be populated by searching for and extracting specific information from external sources. This skill is triggered by requests to fill missing columns in spreadsheets, batch data enrichment tasks, or when working with structured data that requires additional research to complete. It handles Excel file discovery, reading existing data, writing new data to specific cells, and maintaining data integrity across multiple rows.

Smart Excel/CSV file parsing with intelligent routing based on file complexity analysis. Analyzes file structure (merged cells, row count, table layout) using lightweight metadata scanning, then recommends optimal processing strategy - either high-speed Pandas mode for standard tables or semantic HTML mode for complex reports. Use when processing Excel/CSV files with unknown or varying structure where optimization between speed and accuracy is needed.

Automatically generate Excel reports from data sources including CSV, databases, or Python data structures. Supports data analysis reports, business reports, data export, and template-based report generation using pandas and openpyxl. Activate when users mention Excel, spreadsheet, report generation, data export, or business reporting.

Import Excel data into RVT projects. Update element parameters, create schedules, and sync external data sources.

Layout and storytelling guide for marketing analytics executive dashboards.

Create or resume an execution plan - a design document that a coding agent can follow to deliver a working feature or system change

shannon-execution-verifier

Use to systematically validate documents, stories, or processes against defined checklists. Ensures quality and completeness.

Execute one feature (FEAT-XXX) at a time using docs/forge/ideas/<IDEA_ID>/latest/tasks.md as the source of truth. Creates a short workspace checklist and tracks progress so reruns continue automatically.

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The ONLY way to interact with existing projects. Load when user references ANY project by name, ID, or number. Includes: continue, resume, status, progress, check, review, work on [existing project]. NEVER read project files directly.

Execute approved task specifications sequentially with TDD, comprehensive testing, and validation. This skill should be used for implementing tasks from approved specs with full audit trail.

This skill should be used when executing tasks from ai-state/active/tasks.yaml sequentially. It loads tasks, gathers context, implements features with phase-appropriate testing, updates task status in tasks.yaml, organizes tests into ai-state/regressions/ folders, and logs all operations to operations.log. Use after write-plan creates tasks.yaml or when resuming development work.

Complete development lifecycle for GitHub/local issues - branch, implement, test, PR, merge with quality gates

Execute a discrete GitHub issue from a detailed plan file (gi_*.md). Use when implementing a specific, well-defined task with an existing implementation plan in doc/plans/issues/. Handles status tracking, verification, and issue lifecycle.

Plans, creates, and optimizes marketing campaigns including content strategy, social media, email, and analytics. Helps develop go-to-market strategies, campaign messaging, and performance measurement.

Use to execute an implementation plan with automatic sequential/parallel orchestration - handles worktree verification, resume detection, phase dispatch, and quality verification

Verification, drift detection, and snapshot logic for executing-plans

Autonomously execute exploratory implementation of one approach from spike definition, working independently until natural stop. Use when partner provides spike definition and assigns you an approach number to explore in isolation, when comparing multiple implementation alternatives, or when evaluating technical feasibility before committing to an approach

Execute tasks from both GitHub issues and Basic Memory artifacts using unified workflow - supports intelligent source detection and dual-channel status management

Handle common execution failures with specialized recovery strategies. Fix syntax errors, import/dependency issues, path/file problems, permission denial, and connection timeouts. Use proactively when encountering errors or as automatic recovery mechanism.

<purpose>

Implement approved plans into production-ready code. Use when user wants to build, implement, code, or execute an approved plan. Activates when user says 'let's build', 'implement this', 'start coding', or 'execute the plan'.

Transforms research findings into executive-ready briefings. Automatically activated when user mentions 'executive', 'briefing', 'C-suite', 'board', 'leadership', or 'presentation'.

Transform poorly formatted executive summaries into professionally formatted documents matching a specific brand template. Use when the user provides an executive summary (text, markdown, docx, or PDF) and wants it reformatted with precise brand styling including Work Sans fonts, branded color scheme (red #DA291C accent, navy #032340 table headers), specific table formatting, header/footer with logo graphics, and consistent spacing. This skill ensures pixel-perfect replication of the template's typography, tables, bullets, and page layout.

Create concise executive summaries and TL;DR versions of long documents

Create formal executive summaries from GitHub conversations or meeting transcripts. Use when generating leadership-ready summaries that distill key decisions, alternatives, outcomes, and next steps from complex conversations or meetings. Supports GitHub issues/PRs and transcript URIs (Zoom, Teams, etc.). Outputs are saved to Executive Summaries/ with date-organized structure.

Strategic leadership for GabeDA - refines requirements, orchestrates skills, makes architectural decisions, and ensures project coherence. Acts as CEO/CTO/PM to bridge vision and execution.

Code generation and file modification agent with delegation capabilities

Designs deliberate practice exercises applying evidence-based learning strategies like retrieval practice, spaced repetition, and interleaving. Activate when educators need varied exercise types (fill-in-blank, debug-this, build-from-scratch, extend-code, AI-collaborative) targeting learning objectives with appropriate difficulty progression. Creates exercise sets that apply cognitive science principles to maximize retention and skill development. Use when designing practice activities for Python concepts, creating homework assignments, generating problem sets, or evaluating exercise quality.

Break a high-level backlog item into executable sub-items

Generate a new article on a topic. Content is published directly.

Use when planning adoption-to-expansion motions and cross-sell/upsell

Working expectations and documentation practices. Use when capturing learnings or understanding how to work with this codebase.

Create a new expedition with proper ID allocation and template

Track business expenses, categorize spending, manage budgets, and generate financial reports

UX/UI design and user experience

Analyze GRPO training runs for learning dynamics and pipeline performance. Use when diagnosing training issues, reviewing Elo progression, checking throughput, or updating experiment results.

Analyze completed growth experiment results, validate hypotheses, generate insights, and suggest follow-up experiments. Use when experiments are completed, when the user asks about results or learnings, or when discussing what to do next based on experiment outcomes.

Prepare an experiment brief outlining hypothesis, design, success metrics, and operational plan.

Generates a rigorous experiment design given a hypothesis. Use when asked to design experiments, plan experiments, create an experimental setup, or figure out how to test a research hypothesis. Covers controls, baselines, ablations, metrics, statistical tests, and compute estimates.