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    Evidence Chain Completeness Review

    1

    Evidence Chain Completeness Review is a ToolForge Labs workflow for claims, decisions, and actions that require a traceable source-to-conclusion evidence chain.

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    Evidence Chain Completeness Review

    Evidence Chain Completeness Review

    Example session with this skill installed

    A refund of $18,400 was approved because a dashboard screenshot showed “failed deliveries: 92.” The case file contains the screenshot and approval email, but not the dashboard query, date range, account filter, or explanation of how 92 failures produced the $18,400 amount.

    • Read your context and instructions
    • Compiled the evidence chain completeness

    EVIDENCE CHAIN INCOMPLETE

    Case analyzed

    A refund of $18,400 was approved because a dashboard screenshot showed “failed deliveries: 92.” The case file contains the screenshot and approval email, but not the dashboard query, date range, account filter, or explanation of how 92 failures produced the $18,400 amount.

    This review uses only the supplied facts. It does not assume access to production systems, private records, vendor portals, or approvals that were not provided.

    Verified evidence

    • VERIFIED: An $18,400 refund was approved.
    • VERIFIED: A screenshot showed 92 failed deliveries.
    • VERIFIED: The case contains the screenshot and approval email.
    • VERIFIED: Query, date range, account filter, and calculation are absent.

    Concrete findings

    1. The screenshot proves a displayed count, but not the source scope or customer population behind that count.
    2. The financial decision cannot be reproduced because the link from 92 failures to $18,400 is missing.
    3. The current record is not safe to close merely because work has started or a status label says complete; closure must follow the evidence and acceptance condition for this exact case.
    4. The next action should repair the missing decision/evidence boundary without rewriting history or inventing facts that were not available at the time.

    The controlling rule for this case is

    An evidence chain is complete only when each material claim can be traced to a specific source, the source context and time window are known, interpretation is separated from fact, the resulting decision is recorded, and closure evidence proves the action or outcome.

    The supplied facts are sufficient for a concrete case verdict, but not for claiming approvals, delivery, acceptance, or test results that were not supplied.

    Required actions

    1. Capture the dashboard query or source extract with account scope and date range.
    2. Preserve identifiers or aggregate evidence for the 92 failures.
    3. Document the refund calculation including rates, caps, or exclusions.
    4. Link calculation and source evidence to the existing approval.
    5. Define a minimum evidence package for future refunds of this type.

    Deterministic validation

    • A reviewer can reproduce the 92-failure population.
    • The formula produces exactly $18,400.
    • Approval references the same customer and period.
    • No material input exists only in memory.

    Validation must use this exact scenario, not a generic substitute. Preserve the dates, owners, amounts, systems, dependencies, customer promises, or source records that make the case materially different.

    Evidence boundaries

    • UNKNOWN: Date range represented by the screenshot.
    • UNKNOWN: Whether all 92 failures were eligible.
    • UNKNOWN: The compensation rule.
    • UNKNOWN: Whether historical dashboard views are reproducible.

    These unknowns do not erase the conclusion. They define the exact evidence needed before closure without guessing.

    Decision and handoff

    Keep the case open until the stated acceptance condition is evidenced, the responsible owner is identifiable, and any remaining exception is explicit. Record the outcome beside the original evidence so a later reviewer can see what changed, who approved it, and which condition was actually satisfied.

    If the decision changes later, preserve the superseded reasoning rather than silently overwriting it. A later reviewer should be able to reconstruct the chain from original request to evidence, decision, action, and verification.

    Closure rule

    Close only when the requested result is supported by evidence. No completed action, customer acceptance, approval, production verification, or passing test is claimed unless it was actually supplied in this case.

    Additional acceptance detail 1

    Because this case establishes that an $18,400 refund was approved., the closure record should also show that the related action was completed in a traceable way: Capture the dashboard query or source extract with account scope and date range. The evidence should be attached to the same case or linked with a stable identifier, not left only in chat, memory, or an unreferenced status field.

    Additional acceptance detail 2

    Because this case establishes that a screenshot showed 92 failed deliveries., the closure record should also show that the related action was completed in a traceable way: Preserve identifiers or aggregate evidence for the 92 failures. The evidence should be attached to the same case or linked with a stable identifier, not left only in chat, memory, or an unreferenced status field.

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

    What you get

    Audit incident reports for unverified assumptions and logical gaps.Validate compliance claims against specific source documents and time windows.Review technical decisions to ensure they map back to recorded constraints.Identify missing closure evidence in project completion reports.

    About this skill

    Evidence Chain Completeness Review is a ToolForge Labs workflow for claims, decisions, and actions that require a traceable source-to-conclusion evidence chain. Produces a concrete case verdict, verified evidence, missing gates, corrective actions, deterministic validation, and a defensible closure rule without inventing approvals, external access, execution, or outcomes. It performs the supplied case directly, separates verified evidence from unknowns, produces bounded actions, and keeps validation tied to the exact scenario instead of returning an empty template.

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