AI agents enable CSMs to serve more customers, better.
Find, trial, compare, and govern AI agents before hiring
Content
Create, refresh, evaluate, and publish docs, briefs, and reusable knowledge assets.
What team job or business role does the user need filled?
Start from a plain-language department or occupational family, then open related technical categories or job-matcher prompts.
- department or team-role discovery
- plain-language job briefs
- business outcome shortlists
- non-technical browsing
Start from user language
- Refresh docs or README guidance with verifiable source links.
- Create a reusable knowledge asset from existing project material.
Sandbox-first next steps
Content candidates
Showing 12 of 5000. Adjust filters to narrow the review list without losing job context.
Voice AI agents that drive results for you.
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Evaluation of agent systems requires different approaches than traditional software or even standard language model applications. Agents make dynamic decisio…
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This skill analyzes multi-dimensional customer health, churn risk, and expansion opportunities to help CS teams prioritize interventions and growth.
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This skill coordinates CVE research and exploit validation by delegating to specialized subagents for comprehensive vulnerability assessment.
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This skill helps you design and generate AI-powered conversational agents with structured XML instructions, tool callbacks, and evaluation test cases.
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Build AI Agents with Your Existing Python Code!
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This skill autonomously builds and maintains a daily.dev learning feed, ingests new content, and shares actionable insights to boost your knowledge.
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This skill helps you compare hotel room plans, check cancellation policies, and generate a decisive booking handoff with best and fallback options.
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This skill enables real-time web search and premium data access from trusted media brands to power AI agents.
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Browse Data skills for Claude Code, Cursor, Codex and more AI coding agents.
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Transform raw data into analytical assets using ETL/ELT patterns, SQL (dbt), Python (pandas/polars/PySpark), and orchestration (Airflow). Use when building data pipelines, implementing incremental models, migrating from pandas to polars, or orchestrating multi-step transformations with testing and quality checks.
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Review links
Role-family pages stay focused on plain-language job review; complete review records and finalist profile resources stay linked here.
Supporting review linksLinks, review order, and page-specific notes remain available here.
5000 candidates for Content. Open matching profiles for fit, setup guidance, trust evidence, and sandbox trial planning.
- 01Site contextShared review rules
- 02Role familyOpen the focused review record
- 03Profile pageOpen the candidate page
- 04Profile resourcesEvidence, setup, trust, trial, and history files
Use the links and review path below for role-family candidates, job brief context, and finalist profile resources before action.