Build a Vendor Scorecard That Exposes Its Weights in Claude

A weighted scorecard is useful when you need to show how an approved weighting scheme changes a vendor comparison. The result should make the underlying records easier to inspect and the next decision easier to explain. This guide develops a specific weighted scorecard with a source schema, operating rules, a fictional example, and observable review checks. It is intended for someone who already has the underlying material and needs a dependable way to organize it.

Product references checked: 7 October 2026. The examples and implementation specifications below are original editorial guidance. They illustrate expected behavior and have not been presented as a benchmark or as a completed tool tested inside another product.

Define the deliverable and its scope

This is an explainable comparison aid, not automatic supplier selection or a substitute for procurement approval.

Write the acceptance standard before asking Claude for a draft. A reviewer should be able to identify the vendor id, inspect the criterion definition, and understand the eligibility state without guessing what a blank field means. Decide which records belong in the deliverable, which are out of scope, and who can confirm the final interpretation. Keep those choices visible in the working specification rather than leaving the assistant to supply convenient defaults.

Prepare the source package

Gather vendor evidence, criterion definitions, rating scales, weights, and mandatory eligibility rules. Assign source IDs and preserve original wording wherever a small difference could change the outcome. Record the collection date and the version of each source. If two files disagree, keep both references and mark the conflict. Do not replace a disputed value with whichever one produces the cleanest display.

Use a small representative subset for the first draft. Include one ordinary record, one incomplete record, and one record that challenges an important rule. For this task, use the following as the incomplete-record check: Set weights to a total of 110 percent and require a visible validation error. Preserve the original package separately from the assistant's transformed output. A polished result is easier to audit when its IDs still lead back to the original supplied material.

Define the record schema

Treat vendor id as a deliberate part of the data model. Identify the vendor separately from a changing trading name or display label. Keep its representation consistent when you sort, filter, or revise the output. The criterion definition field has a different job: State the evidence needed for each rating and the direction of a better score. Combining these fields into one sentence can hide the distinction the reviewer needs to inspect.

Pay particular attention to approved weight and evidence-backed rating. The former means: A visible editable weight with its unit, owner, and approval state. The latter means: A criterion value linked to the record that supports it, with missing values flagged. Store them separately and label both in the detail view or report. This makes disagreements visible at the exact point where they affect the result instead of burying them in a general note at the bottom.

Apply the task rules

Rule 1. Weights must sum to the declared total, such as one or 100 percent. Reject accidental mixtures of these scales.

Rule 2. Missing evidence must not silently receive a zero or a neutral midpoint rating.

Rule 3. Use eligibility rules before ranking. A high score cannot compensate for a failed mandatory condition.

Rule 4. Keep a sensitivity view showing which criteria explain a ranking change when weights are edited.

Make these rules inspectable alongside the weighted scorecard. Ask Claude to describe how each rule affects a record and what should happen when the supplied data does not establish an answer. A rule written in prose still needs a defined output state. Use an explicit missing, disputed, or not-applicable label where appropriate, and reserve a valid zero or an empty result for cases where it has a defined meaning.

Work through a fictional example

Two fictional vendors are rated from one to five, where higher is better. Alpha scores four for quality and two for support. Beta scores three and four. With weights of 60 percent quality and 40 percent support, Alpha scores 3.2 and Beta scores 3.4. If the approved weights change to 80 and 20 percent, Alpha scores 3.6 and Beta scores 3.2. Display each contribution and both weighting versions. If Alpha fails a mandatory security requirement, its weighted lead does not make it eligible.

Use the example as a review fixture rather than as real operational data. Before generating the output, write down which fields should be populated and which should remain unresolved. Then compare the generated result with that expectation. If Claude supplies an unsupported value, correct the underlying instruction or calculation rule instead of merely editing the one visible record. Otherwise, the same error may return when the next record is processed.

Build the first version

Ask for the simplest interactive artifact that displays the schema and supports the specific review task. Start with the fictional example and an obvious detail panel. Keep the source data separate from display labels and interaction state. A selected row, a filter, or an open panel should change what the reviewer sees, not silently rewrite the underlying evidence. Add editing only to fields that the specification explicitly identifies as user inputs.

For the first interaction pass, prioritize weighted contribution: The normalized rating multiplied by its declared weight, shown per criterion. Then add the eligibility state behavior: A mandatory requirement can disqualify an option independently of the weighted total. Use visible text labels for both. Test the core logic before spending time on animation or visual polish. Provide a keyboard path through the controls and preserve a readable empty state when the selected view has no records.

A reusable prompt

Create a weighted scorecard from the supplied source package. Goal: show how an approved weighting scheme changes a vendor comparison. Use these fields: Vendor ID: Identify the vendor separately from a changing trading name or display label.; Criterion definition: State the evidence needed for each rating and the direction of a better score.; Approved weight: A visible editable weight with its unit, owner, and approval state.; Evidence-backed rating: A criterion value linked to the record that supports it, with missing values flagged.; Weighted contribution: The normalized rating multiplied by its declared weight, shown per criterion.; Eligibility state: A mandatory requirement can disqualify an option independently of the weighted total.. Preserve source IDs. Rules: Weights must sum to the declared total, such as one or 100 percent. Reject accidental mixtures of these scales. Missing evidence must not silently receive a zero or a neutral midpoint rating. Use eligibility rules before ranking. A high score cannot compensate for a failed mandatory condition. Keep a sensitivity view showing which criteria explain a ranking change when weights are edited.. First explain the proposed data model and unresolved inputs. Then build the smallest usable version. Use only supplied facts; label the demonstration fictional. Do not invent approvals, thresholds, owners, or external integrations. Include an empty state and explain the expected result for these checks: Set weights to a total of 110 percent and require a visible validation error. Remove one evidence-backed rating and ensure the vendor's total is unavailable. Change the weights and reconcile each displayed contribution manually.

Review behavior and edge cases

Check 1. Set weights to a total of 110 percent and require a visible validation error. Record the observed result beside the expected result. If the check fails, isolate the affected rule and request a focused correction before rerunning the same case.

Check 2. Remove one evidence-backed rating and ensure the vendor's total is unavailable. Record the observed result beside the expected result. If the check fails, isolate the affected rule and request a focused correction before rerunning the same case.

Check 3. Change the weights and reconcile each displayed contribution manually. Record the observed result beside the expected result. If the check fails, isolate the affected rule and request a focused correction before rerunning the same case.

Repeat the checks after adding another source record or changing the presentation. A working first example does not prove every record is handled correctly. Pay attention to retained selections, stale derived values, and unexplained changes in the number of displayed records. For weighted scorecard work, the reviewer must be able to tell whether a difference comes from new evidence, an edited rule, or merely a changed view.

Maintain the reviewed version

Keep a version label, source cutoff, and short change record with the finished weighted scorecard. Record who approved the rules and which demonstration cases were reviewed. When the source package changes, preserve record IDs and revisit the checks affected by the change. Do not treat yesterday's verified result as evidence that today's replacement input is complete.

Before handing the output to another person, review its audience and the material it contains. Use a sanitized demonstration for general feedback when the real source package is confidential. Explain whether changes are saved, whether the output is a preview, and which source remains authoritative. If persistence or sharing is required, verify that behavior in the actual account and intended environment instead of assuming it from a successful preview.

Frequently asked questions

Sources and related reading

Consult the current primary references for account-specific availability and controls: Current Claude artifact documentation, Claude sharing documentation. The schema, examples, prompts, and review checks here are editorial recommendations rather than documented built-in features.

For broader context, read the related Claude workflow guide.