Eval Rubric logo

Eval Rubric

Organization
Calibre-Labs
eval-rubric

Write or update the eval rubric for an AI agent or AI feature: the pass/fail criteria that define good behavior, in four groups (outcome, trajectory, governance, experience), plus the release thresholds that belong in the PRD. Use this skill whenever someone asks to "write an eval rubric", "define what good looks like", "add evals to my PRD", "what should we evaluate", "turn this PRD into a rubric", "update the rubric from these traces", or shares a PRD, agent spec, system prompt or trace codes and wants evaluation criteria. Also use to audit an existing rubric. Output is an HTML page and a markdown file saved next to the PRD.

Overview

PublisherCalibre-Labs
Repositoryreforge-ai-evals
Skill nameeval-rubric
Stars
94
Forks
9
Bundled files
4
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Calibre-Labs on GitHub. Read the source before you install it.

Installation

Install the Eval Rubric AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Calibre-Labs/reforge-ai-evals/tree/main/skills/eval-rubric
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Calibre-Labs/reforge-ai-evals.git /tmp/reforge-ai-evals
mkdir -p .claude/skills
cp -r /tmp/reforge-ai-evals/skills/eval-rubric .claude/skills/eval-rubric
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Eval Rubric in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Eval Rubric on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Eval Rubric is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Eval rubric skill

An eval rubric is the written definition of good behavior for one AI product. It is a section of the PRD. Every line is a pass/fail check on a single trace. Numbers that hold across many traces (cost, latency, failure rate) are release thresholds and live in their own PRD section.

This skill writes v1 before any traces exist, and v2 after traces have been read. It also audits a rubric someone else wrote.

Read references/worked-examples.md before writing a rubric for the first time in a session. It shows two products taken from v1 to v2.

Pick the mode

The user hasMode
A PRD, spec, system prompt or a product description, and no traces yetv1
A v1 rubric plus trace codes or annotated tracesv2
A rubric and wants feedback on itAudit

If it is unclear, ask one question: "Have you read traces from this agent yet?"

The four kinds of lines

GroupQuestion it answersComes fromTypical owner
Outcome (O)What did it produce, and is it right?Definition of successPM, subject expert, engineering
Trajectory (T)How did it get there?Autonomy table, known risksEngineering
Governance (G)What must it never do, and always do?Tool surface, policy, non-goalsLegal, finance, security
Experience (X)How did it feel to the user in this channel?User and channelDesign

Rules for every line:

  • One behavior per line. If a line has "and" joining two behaviors, split it.
  • Pass or fail on one trace. A reviewer reading a single session can decide.
  • Observable. The evidence is in the trace: an output, a tool call, an argument, a message.
  • About the product, not one demo task. A line written for a coffee order should also hold for the pharmacy pickup. If it mentions the demo's subject, rewrite it.
  • Specific to this product. Generic lines such as "is helpful" or "is safe" are not rubric lines.
  • Governance lines start with "Never" or "Always".
  • Give each line an ID: O1, O2, T1, G1, X1. IDs are stable across versions.

Mode: v1, before traces

Step 1. Find the inputs

Look for a PRD or spec in the working folder first. Read it fully. The rubric derives from four parts of it, described in references/prd-sections.md:

  1. Definition of success
  2. Tool surface, with whether each action is reversible
  3. Autonomy: for each action, does the agent act, confirm first, or escalate
  4. Non-goals and any policy the agent must follow (spend, data, approvals)

Also note the user and channel, because that sets the experience line.

Step 2. Fill the gaps by interview

If any of the four parts is missing, ask for it. Ask at most five questions, in one batch, and only for what you could not find:

  • What does the agent do when it works, in one sentence?
  • Who uses it, through what channel, and what is success measured in (seconds, accuracy, auditability)?
  • What can the agent do? List every tool or action, and say which ones cannot be undone.
  • For the actions that cannot be undone, should it act, confirm first, or hand off to a person?
  • What must it never do? Think spend, data, writes, and requests out of scope.

If the user has policy documents, tool definitions or a system prompt, read them instead of asking. Do not invent tools or policies. If something is unknown, write it under Open questions.

If the PRD has no tool surface or autonomy table, draft both as tables and confirm them with the user before writing the rubric. They are the source of most governance and trajectory lines.

Step 3. Write v1

Write ten to fifteen lines in total, in this order:

  1. Outcome: one or two lines from the definition of success. Task done as requested. Correct against ground truth where one exists.
  2. Governance: as many as the PRD supports. One line for each irreversible action, each policy limit, each data boundary and each non-goal that a user could plausibly ask for. This group is nearly complete on day one.
  3. Trajectory: two lines at most. Only the process rules already known to matter, such as confirming before an irreversible action or stating assumptions.
  4. Experience: one line on tone or brevity for this channel.

Do not try to finish trajectory or experience. The odd paths and the friction are not knowable until traces exist. Say so in the output.

For each line add two short fields:

  • From: the PRD section it derives from.
  • Check: Code if a rule on the trace can decide it, LLM judge if it needs judgment, Human if neither is practical yet. Prefer Code.

Step 4. Write the release thresholds

Separately from the rubric, propose three to five thresholds for the PRD: cost per task, latency, and the failure rate the team will accept at launch. Add a threshold tied to a governance line if a single failure there is unacceptable (for example, zero unapproved writes). Mark every number as a target until there is data. Never put a threshold inside the rubric.

Step 5. Check the draft

Before showing it, test every line:

  • Could two reviewers reading the same trace disagree on pass or fail? Tighten the wording.
  • Does it contain a number that only makes sense across many traces? Move it to thresholds.
  • Is it traceable to the PRD? If not, either the PRD or the line is wrong. Flag it.
  • Would a vendor's default score cover it? If yes, it is probably too generic. Make it specific or cut it.

Then list what v1 cannot know yet: the trajectory and experience lines that only traces reveal.

Mode: v2, after traces

Inputs: the v1 rubric and either trace codes (from the trace-codes skill) or annotated traces.

For each trace code or finding, decide which case it is:

CaseWhat to do
An existing line caught itKeep the line. Note the finding as evidence.
An existing line caused it (too blunt, too broad)Sharpen the line. Keep its ID. Record the old wording.
Nothing covers itAdd a line in the right group with the next free ID.
The behavior is fine and the line is wrongRare. Remove the line only with the user's agreement.

Rules for v2:

  • Mark each changed line New or Sharpened, with the finding that motivated it.
  • A v2 mostly adds and sharpens. If the draft removes more than one line, stop and check.
  • New lines must still be about the product, not the trace that produced them.
  • Recalibrate the release thresholds against real cost and latency if the traces include them. Propose a new threshold only when a finding justifies one.
  • Open with a short paragraph: how many lines were added and sharpened, and what the traces showed that v1 missed.

Mode: audit

Check an existing rubric against the rules above and report, per line: keep, rewrite (with the rewrite), split, move to release thresholds, or cut. Then list what is missing by group. A rubric with no governance lines for an agent that can write, spend or send is incomplete.

Output

Save two files next to the PRD (or in the working folder if there is no PRD):

  • <product>-rubric-v<N>.md: the rubric as a table per group, then the release thresholds, then open questions.
  • <product>-rubric-v<N>.html: the same content as a page, built from references/rubric-template.html. Fill the placeholders and keep the structure.

In the reply, give the count of lines per group, the two or three lines most worth debating with stakeholders, and what to do next:

  • After v1: generate traces and read them, then run trace-codes.
  • After v2: turn lines into scorers with eval-code (lines marked Code) and eval-llm-judge (lines marked LLM judge).

Working notes

  • The rubric is the PM's document. Draft it, then ask the user to decide the lines that involve a tradeoff. Do not present a rubric as final.
  • Keep v1 short. A long v1 is usually trajectory and experience lines that were guessed.
  • Who the product is for changes the rubric more than what it does. A consumer agent usually guesses and discloses. An enterprise agent usually asks and shows its work. See the two worked examples.
  • If the agent has no irreversible actions, say that governance will be short and consists of policy lines only.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Eval Rubric AI skill do?

Write or update the eval rubric for an AI agent or AI feature: the pass/fail criteria that define good behavior, in four groups (outcome, trajectory, governance, experience), plus the release thresholds that belong in the PRD. Use this skill whenever someone asks to "write an eval rubric", "define what good looks like", "add evals to my PRD", "what should we evaluate", "turn this PRD into a rubric", "update the rubric from these traces", or shares a PRD, agent spec, system prompt or trace codes and wants evaluation criteria. Also use to audit an existing rubric. Output is an HTML page and a...

Why use Eval Rubric on TypingMind?

Because you install it once and use it with any model. Eval Rubric is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Eval Rubric in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Calibre-Labs/reforge-ai-evals/tree/main/skills/eval-rubric. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Eval Rubric?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Eval Rubric?

As many as you like. As long as a model supports skills, you can use Eval Rubric with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Eval Rubric AI skill free?

Yes. It is published on GitHub by Calibre-Labs under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇