Agent Workflows · By seb1n

Design and verify auditable human oversight, approval gates, escalation paths, and safe state transitions for AI agent workflows.

seb1n/awesome-ai-agent-skills

Design, implement, harden, and verify Model Context Protocol (MCP) servers with precise tool contracts, least-privilege authorization, safe transports, structured errors, and interoperability tests.

seb1n/awesome-ai-agent-skills

Design reproducible evaluations for AI agents with representative task sets, explicit rubrics, appropriate graders, baselines, regression gates, and failure analysis.

seb1n/awesome-ai-agent-skills

Design and operate bounded multi-agent workflows with task decomposition, dependency graphs, ownership, handoff contracts, shared-state controls, approvals, recovery, and synthesis.

seb1n/awesome-ai-agent-skills

Place trusted contextual information into prompts or agent state using explicit boundaries, provenance, and templates.

seb1n/awesome-ai-agent-skills

Optimize a complete candidate context package by deduplicating, filtering, ordering, and allocating its token budget.

seb1n/awesome-ai-agent-skills

Rank an existing set of context chunks by relevance, diversity, freshness, and utility.

seb1n/awesome-ai-agent-skills

Retrieve relevant information from a knowledge base using semantic, keyword, or hybrid search to ground a query.

seb1n/awesome-ai-agent-skills

Compress selected context to a target token budget while preserving decisions, evidence, constraints, and unresolved questions.

seb1n/awesome-ai-agent-skills