sequential agent workflow builder

    1

    Architect high-reliability multi-agent pipelines with formal contracts, validation gates, and revision loops.

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    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIGitHub CopilotGitHub CopilotGemini CLIGemini CLI+20 more

    sequential agent workflow builder

    Example session with this skill installed

    Design a 4-stage sequential agent pipeline for processing customer support emails, from classification to final response generation, including quality gates and escalation rules.

    • Read your context and instructions
    • Compiled the sequential agent workflow
    • Generated the UI component

    I have designed a 4-stage sequential workflow for customer support email processing. This specification includes strict input/output contracts, validation gates, and clear escalation paths for low-confidence classifications.

    Support Email Processing Workflow

    graph TD
    S1[stage-01-triage] --> G1{gate-01-02}
    G1 -->|Pass| S2[stage-02-extract]
    G1 -->|Fail| E1[Escalate to Human]
    S2 --> G2{gate-02-03}
    G2 -->|Pass| S3[stage-03-draft]
    G2 -->|Fail| R1[Revision Loop S1]
    S3 --> G3{gate-03-04}
    G3 -->|Pass| S4[stage-04-qa]
    S4 --> G4{gate-04-out}

    Stage Definitions

    Stage IDAgent RoleOutput ContractValidation Gate
    stage-01-triageClassifier{category: string, priority: int, sentiment: float}priority in [1,2,3]
    stage-02-extractData Extractor{order_id: string, customer_id: string, issue_summary: text}order_id matches regex
    stage-03-draftWriter{response_body: text, tone: string, cited_docs: list}response_body.length > 50
    stage-04-qaReviewer{approved: bool, score: float, feedback: text}score >= 0.85

    Revision & Escalation Policy

    Revision Loop: If gate-03-04 fails, the QA agent sends a revision_message to the Writer agent. Max 2 attempts before escalation.

    Escalation: Any artifact with a classification confidence < 0.7 at stage-01 is routed to the human_coordinator_agent.

    • Traceability: All transitions are logged with an upstream_digest to ensure data integrity across the pipeline.

    Next steps

    • Implement the JSON Schemas for the defined output contracts in your orchestration framework.
    • Configure the human_coordinator_agent webhook for the escalation triggers.
    • Run the "Happy Path" test scenario to verify agent handoff latency.

    sequential-agent-workflow-builder.tsx

    TSX · React component

    Generated

    Example file from a real run - the skill writes it into your workspace.

    Connects securely to your tools. The creator never sees your data.

    What you get

    Define formal I/O contracts between agents to prevent data corruption.Implement validation gates to stop low-quality results from propagating.Establish bounded revision loops for automated error correction.Create auditable traceability logs for multi-stage agent decisions.

    About this skill

    The problem

    Multi-agent systems often fail when low-quality outputs from one agent propagate downstream, causing a chain reaction of errors. Managing state, handoffs, and error recovery in complex agent pipelines becomes unmanageable without a formal contract-driven architecture.

    What it does

    • Generates strict sequential stage definitions with specialized roles and clear input/output contracts.
    • Designs automated validation gates to block malformed or low-confidence artifacts before they reach downstream agents.
    • Configures bounded revision loops and feedback paths to resolve quality issues without manual restarts.
    • Defines explicit escalation rules and conflict resolution protocols for handling autonomous failures.
    • Specifies append-only traceability schemas to maintain a full audit trail of every agent decision and state transition.

    Why this beats prompting it yourself

    Building reliable agent chains requires rigorous systems engineering, not just prompting. This skill enforces a structured framework that prevents common pitfalls like circular dependencies, state drift, and unhandled edge cases, delivering a blueprint that is ready for implementation in your orchestration layer.

    Use cases

    • Content generation pipelines requiring extraction, analysis, drafting, and QA stages.
    • Data processing workflows where accuracy and confidence scores must meet specific thresholds.
    • Legal or financial document analysis needing multi-stage verification and human-in-the-loop escalation.
    • Complex software engineering tasks involving research, implementation, testing, and documentation stages.

    Known limitations

    Focuses on synchronous sequential pipelines. Asynchronous or highly parallel branch designs require explicit manual annotation within the workflow specification.

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
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