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    Compliance Matrix Builder

    1

    Builds rigorous shall/will/should compliance matrices from SOWs and drafts, flagging evidence gaps without fluff.

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    Compliance Matrix Builder

    Compliance Matrix Builder

    Example session with this skill installed

    Build the compliance matrix for the 'Harbor County Cloud Migration' project. Use sow.md and draft_v1.md. Look for shall, must, and should. Output to compliance_matrix.md.

    • Read your context and instructions
    • Compiled the compliance matrix builder

    I have processed the Harbor County Cloud Migration SOW and Draft V1. I extracted 5 requirements and identified 2 gaps where the draft lacks sufficient evidence or mechanisms.

    Compliance Matrix: Harbor County Cloud Migration

    Offeror: [Offeror]
    Volume ID: Technical Volume
    SOW Row Count: 5
    Gap Count: 2

    SOW idModalRequirementSectionEvidenceGap
    1.1.2shalldaily encrypted backups to off-site2.1tagged paragraphnone
    1.1.3mustredundant power supply for onsite hardware2.2heading onlyno mechanism
    2.0.1willgovernment provides access credentialsN/Anonebuyer-owned
    3.2.4shoulduse AES-256 for data at rest4.1paraphraseno check
    3.2.5shallmultifactor authentication for all admins4.2tagged paragraphnone

    Gap Register

    • 1.1.3: no mechanism. Section 2.2 identifies the requirement but does not describe how redundancy is achieved.
    • 3.2.4: no check. Section 4.1 mentions AES-256 but lacks a validation or reporting artifact.

    Notes

    • UNN-001: Requirement found in SOW Section 4 without a formal ID; assigned temporary ID for tracking.
    • Row 3.2.4: Modal should was preserved and not promoted to shall.

    Next steps

    1. Review Section 2.2 to add specific hardware specifications for the power supply mechanism.
    2. Update Section 4.1 to include the specific log or audit report that verifies encryption standards.
    3. Verify if UNN-001 requires a formal clarification request to the buyer.

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    About this skill

    The problem

    Manual compliance mapping is slow, prone to missing "should" vs "shall" distinctions, and often fails to identify specific gaps in draft evidence. Developers and proposal managers struggle to maintain a source of truth between evolving SOW requirements and technical drafts.

    What it does

    • Extracts every requirement from SOW/PWS files based on specific modals like shall, must, will, should, and may.
    • Inventories draft documents to find explicit compliance tags, tables, and heading matches.
    • Maps requirements to draft sections with evidence scoring (tagged paragraph, heading only, paraphrase, or none).
    • Flags concrete gaps including missing mechanisms, missing boundaries, or missing checks without inventing prose.
    • Generates a structured compliance matrix with a header summary, gap register, and unnumbered requirement notes.

    Why this beats prompting it yourself

    Generic prompts often hallucinate compliance coverage or collapse nuanced modals into a single category. This skill enforces a rigorous three-part test (mechanism, boundary, check) for every requirement and prevents the agent from "fixing" gaps with invented text, ensuring an honest assessment of proposal readiness.

    Use cases

    • Generating a pink-team compliance matrix from a raw SOW and early-stage draft.
    • Performing a book-level coverage check before a final color review to ensure all "should" requirements are met.
    • Identifying duplicate claims where multiple sections attempt to own the same SOW requirement.
    • Extracting unnumbered requirements from poorly formatted solicitation documents.

    Known limitations

    Requires structured input files for the SOW and draft. It does not write missing sections or perform page-count reduction, as these are handled by separate specialized skills.

    How to use

    Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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