Judge the work against the same standard.
ProductRubric helps product teams make better decisions about the work in front of them. Whether a design is ready to ship, whether a survey can be trusted, whether findings are strong enough to act on: those calls usually rest on whoever happens to review the work, using whatever criteria they improvise in the moment.
ProductRubric is an open library of evaluation rubrics that replaces the improvisation. Your AI assistant applies a rubric to the work itself, a screen, a design board, a study plan, a questionnaire, or a readout, and returns a structured review, the same shape of review in Claude, ChatGPT, Grok, Cursor, or any other tool, every time.
Connect the MCP server
The whole library is served over MCP. Add this address to your AI tool and it can list the rubrics, fetch the one you ask for, and apply it in your chat. No account and no key.
https://mcp.productrubric.com
Where the address goes
Settings, Connectors, Add custom connector. Name it ProductRubric and paste the address.
Settings, Connectors, then add a custom connector and paste the address. On paid plans, developer mode needs to be on, under Advanced settings.
Go to grok.com/connectors, choose New Connector, then Custom, and paste the address. In Grok Bot, you can also send the bot “Add this MCP server: https://mcp.productrubric.com” in chat.
Settings, MCP, Add new global MCP server. Paste the address as the server URL.
Ask your AI to add this server for you. Agent tools can do this themselves. If yours keeps connectors in its settings instead, it will walk you through the same two steps: add a custom connector, paste the address.
A rubric, running in a chat
This is the whole product in one exchange, adapted from the library’s worked example: the Survey Review rubric run on the sample questionnaire in the repository.
Survey Review. 12 questions reviewed: 1 invalidating, 8 biasing, 1 burden, 2 sound.
Q1 (Invalidating): “How much do you love using Ledgerline?” presupposes the feeling it claims to measure, so the survey’s headline number is manufactured. Suggested revision: “How satisfied are you with Ledgerline so far?”, on a balanced scale.
Q6 (Biasing): “Do you agree that our pricing is unfair for freelancers?” plants its conclusion. Suggested revision: “How fair do you think Ledgerline’s pricing is for freelancers?”
Highest impact fix: replace Q1. As written, the result the team will quote most is the one the question invented.
Rubric summary
Rubric: Survey Review v1.0 · Date: Oct 20, 2026 · Artifact: day-30-survey.pdf
Questions: Reviewed 12 · Invalidating flaws 1 · Biasing flaws 8 · Burden flaws 1 · Sound 2
Result: 10 of 12 questions need revision before the survey is fielded
Every flawed question gets a rating, the criterion it breaks, and a rewritten version ready to drop into the survey. Every report closes with the same summary block, so a team can keep them across runs and watch the flaw counts fall.
Watch it happen
Short screen recordings, trimmed for length, with the waiting sped up and nothing else changed. One shows an assistant connecting the library, one shows a designer asking a plain question about a homepage, and one shows a researcher handing over a study plan. Choose a scene and press play.
One message with the address, and the assistant sets the connection up itself. No account, no key, and nothing to install. This was recorded in Muse; in Claude, ChatGPT, Cursor, or Grok, the same address goes into the connector settings listed above.
What is a rubric?
A rubric is a review written down before the work arrives: the criteria to judge against, the scoring to use, and the format the verdict comes back in. Product teams already work from rubrics informally, in critique habits, heuristic evaluation, and survey methodology. Those traditions are frameworks. A rubric takes a framework, an established one or your own, and turns it into instructions an AI can follow consistently, so the standard survives the person who brought it.
Each rubric here is one plain Markdown file, and each one also states plainly what it cannot judge.
Who runs a rubric, and when
Run one on a screen or a flow before a crit, before a design review, or at handoff, and walk in already knowing where the work is weak and where it holds up.
Run one on the study plan before recruiting starts, on the questionnaire before it fields, and on the readout before it goes to stakeholders. The cheap moment to catch a leading question is before anyone has answered it.
The ship decision, and the call on whether findings are strong enough to act on, usually land on your desk. Run the same rubric the team ran and you see the design or the readout the way its toughest reviewer would, before the meeting where the decision gets made.
Run one on the positioning before messaging is built on it, on the messaging before the homepage and the deck repeat it, on the launch plan while it can still change, and on the battlecard before a rep trusts it in front of a buyer.
Your standards stop living in your head and in old feedback threads. Written down as rubrics, they are applied the same way in every review, whoever runs it and whichever AI they use.
The criteria a staff designer or a research lead would apply, available in the room even when there is no staff designer or research lead in it. If you are also the one building, that covers the Accessibility Review on the interface you shipped and the Copy Review on the error messages and empty states nobody was assigned, because on a small team that person is you.
Product design
Run one before a design ships, before a crit, or at handoff. Select a rubric for its full description.
- Simple
- One screen and one narrow question. Quick to run, on any current model.
- Standard
- One screen or flow, judged against structured criteria, with a fuller report.
- Deep
- Needs more than the artifact itself, such as a full board with its rationale, or context the rubric asks you for before it judges.
Design Principles Score Standard Scores a screen or flow against seven product design principles.
Inclusive Design Audit Standard Audits a screen or flow against five inclusive design principles for cultural fit.
Accessibility Review Standard Reviews a screen’s design for accessibility problems visible in a screenshot or description.
Copy Review Standard Reviews every piece of text on a screen and suggests a better revision for each one.
Five Second Test Simple Predicts what a first-time visitor remembers after five seconds, and what they miss.
Attention Prediction Simple Predicts the three places a viewer’s eye lands first on a screen.
Design Quality Deep Reviews a design board with its rationale against seven dimensions of design quality.
Product research
Run one before a study is fielded, or before findings are presented to stakeholders. Select a rubric for its full description.
Study Plan Review Deep Reviews a study plan before it is fielded and judges whether it is ready.
Survey Review Standard Reviews a questionnaire question by question and rewrites the flawed ones.
Findings Review Standard Reviews a readout and checks whether every claim traces to evidence.
Competitive Analysis Review Standard Reviews a competitive analysis: the set, the evidence, and honest strengths.
Product management
Run one before a team commits: to building, to a roadmap, or to a date. Select a rubric for its full description.
PRD Review Deep Reviews a requirements document before a team builds against it.
Roadmap Review Standard Reviews a roadmap for outcomes, strategy traceability, and honest dates.
Problem Statement Review Simple Reviews a problem statement: a specific person, evidence, and no smuggled solution.
User Story Review Simple Reviews a user story and its acceptance criteria against INVEST.
Project Plan Review Deep Reviews a project plan before anyone commits to its dates.
Product marketing
Run one before positioning, messaging, a launch, or a battlecard reaches the people who will repeat it. Select a rubric for its full description.
Positioning Review Standard Reviews positioning against the five components of effective positioning.
Messaging Review Standard Reviews a messaging document: insight first, proof attached, a clear ask.
Launch Plan Review Deep Reviews a launch plan: tier, audiences, readiness, and rollback.
Battlecard Review Simple Reviews a battlecard: claims sourced and dated, usable mid-call.
Open, and growing
ProductRubric is an open project. The library is created and maintained by David Nguyen, and it grows through contributions. If your team has a review it runs again and again, you can write it as a rubric in the shared format and propose it to the library. Rubrics based on a published framework stay credited to that framework’s author, and contributed rubrics carry their writer’s name. The builder writes the file for you from a form, if you would rather not start from the blank template.
Three ways to use the library
Use the files
Open any rubric from the repository, give it to your AI with the work, and ask for the evaluation. Works today, with no setup.
Get the files on GitHubInstall the Skills
Each rubric also ships as an installable Skill, so your assistant can pick the right evaluation on its own.
Get the Skill packConnect the MCP server
Point your AI tool at the hosted server above, or run the same server locally against your own folder of rubrics.
Get the server addressDESIGN.md tells an AI how to create the design. PRODUCTRUBRIC.md tells an AI how to judge it.
A rubric standardizes the questions, the criteria, and the shape of the report. It cannot standardize the judgment inside the answers, which depends on the model you run and the material you give it. Treat a result as a structured review by a capable reader, not as a measurement.
Questions
What can I use this for?
Getting a proper review of product work before it goes out, from the AI assistant you already use. Designers run rubrics on screens and flows before a critique. Researchers run them on study plans and surveys before anything fields, while the fixes are still cheap. Product managers run them on PRDs, roadmaps, and project plans before the team commits to them. Marketers run them on positioning, messaging, and launch plans before they reach the market. Every run comes back in the same shape: what holds up, what needs work, and what to fix first.
Is ProductRubric an AI tool that reviews my work for me?
No. ProductRubric contains no AI. It is a library of written standards. Your own AI assistant does the reviewing, applying the rubric you choose, and the material you evaluate never passes through ProductRubric.
How is this different from asking an AI for a critique directly?
A direct ask improvises the criteria in the moment, so the same work gets a different review every time. A rubric fixes the criteria, the scoring, and the report format in writing, so reviews are consistent, comparable across tools and across time, and honest about what they could not judge.
Can my team track whether our work is improving?
Yes. Every report ends with a Rubric summary: the rubric and its version, the date, the artifact, and the result tallied in the rubric’s own terms, criteria at each grade, flaws at each rating, any gate criteria not met. Keep the summaries across runs and the pattern shows itself: the same criterion failing less often, readiness verdicts arriving with fewer fixes, fewer biasing questions per survey. One run is one structured judgment and carries the noise of one; the trend across runs is the signal.
Which AI assistants does it work with?
Any assistant that can read text or connect to an MCP server, including Claude, ChatGPT, Grok, and Cursor. The product design rubrics need an assistant that can see images. The product research, product management, and product marketing rubrics judge documents, so any text assistant can run them.
Do I need an account or an API key?
No. The hosted MCP server is open, the files are on GitHub, and there is nothing to sign up for.
Does ProductRubric see my designs or my data?
No. The server only sends rubric text out. Your screenshots, boards, and documents stay in your own chat with your own AI provider.
What does it cost?
Nothing. The rubric files are licensed CC BY 4.0 with credit to their authors, and the server code is Apache 2.0.
Can I write a rubric for my own team?
Yes. The format is documented in the repository. You can run your own rubrics locally through the same MCP server, install them as Skills, or propose them to this library.