Data & AI skills

Expert en data lakes (S3, Delta Lake, Iceberg, schema evolution, governance)

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Expert en croissance data-driven (experimentation, metrics, dashboards, correlation analysis)

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Data Engineer IA — Expert en pipelines de données (ETL, data lakes, dbt, Airflow, streaming). Construit des pipelines fiables, scalables et auditable.

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Data scientist v3 — ML, deep learning, NLP, CV, experimentation, MLOps

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Expert en data engineering (ETL, Airflow, dbt, data lakes, streaming pipelines, data quality)

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Data Scientist IA — Expert en data science (pandas, numpy, scikit-learn, EDA, feature engineering, statistical analysis)

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Expert en data warehousing (Snowflake, BigQuery, Redshift, star schema, slowly changing dimensions)

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Data Labeling Specialist IA — Expert en annotation de données (outils, contrôle qualité, agreement inter-annotateurs, active learning)

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Expert en annotation de données avancé (annotation, quality, active learning, consensus, tools)

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Data-driven growth v3 — experimentation, metrics, dashboards, correlation analysis

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Expert en gouvernance des données (catalogage, lineage, règles qualité, conformité, stewardship)

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Expert en data lakes avancé (S3, Delta Lake, Iceberg, partitioning, governance, catalog, query optimization, lakehouse)

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Expert en data mesh (domain ownership, data products, self-serve, gouvernance fédérée)

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Analytics Specialist IA — Expert en analytics (GA4, Mixpanel, Amplitude, event tracking, dashboards).

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Expert en RAG agentique (retrieval multi-étapes, self-query, chunking adaptatif, tool-augmented generation)

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WHAT: Generate Codex-authored HTML insights from local Codex sessions and telemetry. WHEN: Use when the user asks for Codex usage analytics, workflow patterns, session summaries, prompting help, or recommendations for improving how they use Codex.

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Convert the canonical markdown+JSON deliverable of any SfSkills runtime agent into Excel, PDF, CSV, Notion card, ServiceNow ticket, or similar downstream format WITHOUT polluting the consumer's project with new dependencies or regenerating from the agent's source logic. NOT for authoring new agent output formats (use DELIVERABLE_CONTRACT.md). NOT for data-export SOQL (use bulk-api-2-patterns).

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Expert content marketer specializing in content strategy, SEO optimization, and engagement-driven marketing. Masters multi-channel content creation, analytics, and conversion optimization with focus on building brand authority and driving measurable business results.

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MUST USE for building FastAPI/REST API applications with Aerospike database (aerospike-py Rust/PyO3 async client). Covers AsyncClient lifespan management, FastAPI Depends injection, aerospike_py exception-to-HTTP-status mapping (RecordNotFound→404, RecordExistsError→409, BackpressureError→503, AerospikeTimeoutError→504), POLICY_EXISTS_CREATE_ONLY/UPDATE_ONLY for CRUD semantics, NamedTuple attribute access (record.bins not tuple unpacking), client.ping() readiness probe, batch_read returning dict, batch_write with in_doubt retry signal, and global AerospikeError handler. Triggers on: FastAPI + Aerospike, REST API + aerospike-py, CRUD API with Aerospike, client.ping() health probe, batch_read/batch_write endpoint, web server/HTTP service backed by Aerospike NoSQL, uvicorn + Aerospike.

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Use when designing how an Agentforce agent extracts structured input parameters (slots) from a user's natural-language utterance to invoke an action. Triggers: 'agent extract date from user', 'agent action argument extraction', 'agentforce slot filling', 'agent invocable input mapping', 'agent fails to fill required parameter'. NOT for action authoring (use agentforce/agent-actions) or for prompt-template variable binding (use agentforce/prompt-builder-templates).

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Implement data handling for Adobe APIs including PII redaction in logs, Firefly content policy compliance, PDF document data classification, and GDPR/CCPA data subject access requests via Adobe Privacy Service. Trigger with phrases like "adobe data", "adobe PII", "adobe GDPR", "adobe data retention", "adobe privacy", "adobe content policy".

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Creates TanStack Query hooks for API features with authentication. Use when connecting frontend to backend endpoints, creating data fetching hooks.

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This skill should be used when the user says "add a billing agent", "add a bookkeeping agent", "set up a support tier-1 agent", "add a recruiting agent", "add a compliance agent", "add a CRM agent", "add a contracts agent", "add an analytics agent", "add a marketing email agent", "add a CMS agent", "scaffold a function-specific agent", or wants to add a single business-function agent backed by a verified-write MCP integration. Each agent ships with explicit scope, "what this will NOT do" constraints, and recommended human-in-the-loop checkpoints.

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Fetch any X/Twitter post as clean LLM-friendly JSON. Converts x.com, twitter.com, or adhx.com links into structured data with full article content, author info, and engagement metrics. No scraping or browser required.

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