Evals Validate

Q: Why use Evals Validate on TypingMind?

Because you install it once and use it with any model. Evals Validate 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.

Q: How do I install Evals Validate in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tikalk/adlc-team-skills/tree/main/skills/evals/evals-validate. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Q: Which AI models can use Evals Validate?

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.

Q: How many AI models can I use with Evals Validate?

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

Q: Is the Evals Validate AI skill free?

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

Q: 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.

Q: 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.

Organization

tikalk

evals-validate

Use when a goldset with graders is ready to run — executes the evaluation pyramid and validates evaluator quality (SLA compliance, TPR/TNR, statistical accuracy).

Overview

Publisher	tikalk
Repository	`adlc-team-skills`
Skill name	`evals-validate`
Stars	144
Forks	2
Bundled files	2
License	MIT
Links	Skill source Repository

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.
2 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by tikalk on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/tikalk/adlc-team-skills/tree/main/skills/evals/evals-validate
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.

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/tikalk/adlc-team-skills.git /tmp/adlc-team-skills
mkdir -p .claude/skills
cp -r /tmp/adlc-team-skills/skills/evals/evals-validate .claude/skills/evals-validate

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Evals Validate 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 Evals Validate 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 Evals Validate 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.

evals-validate

What this skill does

Conducts comprehensive validation of the implemented evaluation system following EDD principles to ensure production readiness through statistical analysis, performance verification, and quality assurance.

Output:

Statistical Validation - TPR/TNR analysis, accuracy metrics, confidence intervals
Performance Validation - SLA compliance verification for evaluation pyramid tiers
Quality Assurance - Goldset integrity, example balance, coverage analysis
Holdout Dataset Validation - Unbiased accuracy assessment on reserved test set
Auto-handoff to /evals-analyze for closed loop trajectory analysis

Key EDD Principles Applied:

Principle IV: Evaluation Pyramid - Tier performance SLA validation (Tier 1 <30s, Tier 2 <5min)
Principle II: Binary Pass/Fail - Statistical compliance verification
Principle IX: Test Data as Code - Holdout dataset validation integrity
Principle III: Error Analysis - Pattern stability validation

When to use

After /evals-implement: Execute the evaluation suite and measure quality
CI/CD Pipeline gate: Run evaluations before release to ensure no regressions
Periodic audit: Verify evaluator accuracy on holdout data to check for model drift

When NOT to use

Evaluator not generated: Run /evals-implement to build grader files first
Analysing failure traces: Use /evals-analyze to extract deep insights from run results

Process

User Input

text
$ARGUMENTS

--holdout-only — Validate only on holdout dataset (unbiased validation)
--performance-only — Skip statistical analysis, focus on SLA compliance
--metrics METRICS — Specific metrics to validate (tpr, tnr, accuracy, performance)

Execution Steps

Phase 1: Execute Evaluations

Runs the underlying framework CLI directly:

PromptFoo: npx promptfoo eval --config evals/promptfoo/config.js
DeepEval: pytest evals/deepeval/ -v or python evals/deepeval/config.py

Phase 2: Compute Statistical Validation

Parse generated results JSON from evals/results/.
Calculate True Positive Rate (TPR) and True Negative Rate (TNR).
Calculate overall accuracy with 95% confidence intervals.
Ensure no Likert scales or numerical scores leak into results.

Phase 3: SLA Compliance Check

Measure execution times for Tier 1 and Tier 2.
Verify Tier 1 completes under 30 seconds.
Verify Tier 2 completes under 5 minutes.
Check headroom analysis (SLA budget consumed).

Phase 4: Write Validation Report

Write validation results to evals/results/validation_report.md.
Include pass/fail counts, TPR/TNR table, SLA timings, and holdout set results.

Phase 5: Auto-Handoff

Trigger /evals-analyze to close the loop.

Verification

Evaluation execution successfully completed with results JSON written to evals/results/
evals/results/validation_report.md created with TPR/TNR and SLA metrics
Statistical metrics calculated with confidence intervals
Headroom and SLA compliance verified
Handover summary lists results and validation report path

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 Evals Validate AI skill do?

Use when a goldset with graders is ready to run — executes the evaluation pyramid and validates evaluator quality (SLA compliance, TPR/TNR, statistical accuracy).

Why use Evals Validate on TypingMind?

Because you install it once and use it with any model. Evals Validate 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 Evals Validate in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tikalk/adlc-team-skills/tree/main/skills/evals/evals-validate. 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 Evals Validate?

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 Evals Validate?

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

Is the Evals Validate AI skill free?

Yes. It is published on GitHub by tikalk 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.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

evals-validate

What this skill does

When to use

When NOT to use

Process

User Input

Execution Steps

Phase 1: Execute Evaluations

Phase 2: Compute Statistical Validation

Phase 3: SLA Compliance Check

Phase 4: Write Validation Report

Phase 5: Auto-Handoff

Verification

Bundled files

Frequently asked questions

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