Dogfood Exploratory QA
vercel-labs/agent-browser
Explores a web app with the agent-browser CLI to find bugs and UX problems, then writes a report with screenshots, repro videos and step-by-step reproduction for each issue.
Prompt engineering regression test matrix register: baseline outputs, semantic drift thresholds, judge evaluations, and golden dataset.
Install AI Prompt Regression Testing
$ npx skills add sickn33/agentic-awesome-skills --skill ai-prompt-regression-testing -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install sickn33/agentic-awesome-skills ai-prompt-regression-testing --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai-prompt-regression-testing .claude/skills/ai-prompt-regression-testing && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "ai-prompt-regression-testing" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/ai-prompt-regression-testing into .claude/skills/ai-prompt-regression-testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-prompt-regression-testing", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/ai-prompt-regression-testingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add sickn33/agentic-awesome-skills --skill ai-prompt-regression-testing -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install sickn33/agentic-awesome-skills ai-prompt-regression-testing --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ai-prompt-regression-testing .agents/skills/ai-prompt-regression-testing && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ai-prompt-regression-testing" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/ai-prompt-regression-testing into .agents/skills/ai-prompt-regression-testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-prompt-regression-testing", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add sickn33/agentic-awesome-skills --skill ai-prompt-regression-testing -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install sickn33/agentic-awesome-skills ai-prompt-regression-testing --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ai-prompt-regression-testing .cursor/skills/ai-prompt-regression-testing && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "ai-prompt-regression-testing" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/ai-prompt-regression-testing into .cursor/skills/ai-prompt-regression-testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-prompt-regression-testing", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/sickn33/agentic-awesome-skills.git --path skills/ai-prompt-regression-testing--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add sickn33/agentic-awesome-skills --skill ai-prompt-regression-testing -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install sickn33/agentic-awesome-skills ai-prompt-regression-testing --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ai-prompt-regression-testing .gemini/skills/ai-prompt-regression-testing && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "ai-prompt-regression-testing" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/ai-prompt-regression-testing into .gemini/skills/ai-prompt-regression-testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-prompt-regression-testing", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install sickn33/agentic-awesome-skills ai-prompt-regression-testingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add sickn33/agentic-awesome-skills --skill ai-prompt-regression-testing -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ai-prompt-regression-testing .github/skills/ai-prompt-regression-testing && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "ai-prompt-regression-testing" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/ai-prompt-regression-testing into .github/skills/ai-prompt-regression-testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-prompt-regression-testing", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add sickn33/agentic-awesome-skills --skill ai-prompt-regression-testing -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install sickn33/agentic-awesome-skills ai-prompt-regression-testing --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ai-prompt-regression-testing .opencode/skills/ai-prompt-regression-testing && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "ai-prompt-regression-testing" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/ai-prompt-regression-testing into .opencode/skills/ai-prompt-regression-testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-prompt-regression-testing", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
ai-prompt-regression-testing- GitHub stars
- 47k
- Used in
- 1 other repo
- Token cost
- ~1.3k tokens
- SKILL.md length
- 504 words
- Files
- 1
- Skills in repo
- 1,497
- Repo updated
- First seen
- Licence
- MIT
At a glance
Prompt engineering regression test matrix register: baseline outputs, semantic drift thresholds, judge evaluations, and golden dataset.
- Works in 3 steps: Define the parameters, thresholds, and… → Select appropriate boundary enforcement… → Export standardized artifacts (CSV…
- Tasks that involve QA and bug reports
- SKILL.md covers Overview, When to Use This Skill, How It Works and Field Reference, plus 9 more sections
- Calls claude and gemini
What it does
AI Prompt Regression Testing is an agent skill from sickn33/agentic-awesome-skills. Prompt engineering regression test matrix register: baseline outputs, semantic drift thresholds, judge evaluations, and golden dataset.
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Testing & QA, covering QA and bug reports. It works with SQL. The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.
When your agent uses it
- Tasks that involve QA and bug reports
Example prompts
- “/ai-prompt-regression-testing”
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- Define the parameters, thresholds, and identity bindings required for the target operational register.
- Select appropriate boundary enforcement values from validated enum select sets.
- Export standardized artifacts (CSV table, SQL DDL, JSON Schema) to integrate into validation CI pipelines.
What it can do on your machine
Read from SKILL.md and the folder at commit b84d35a. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
claudegemini
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
AI Prompt Regression Testing loads about 1.3k tokens when it runs. Until then it costs about 41 tokens; SKILL.md has 504 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from sickn33/agentic-awesome-skills at commit b84d35a, republished under its MIT licence (© sickn33). 504 words, ~1,340 tokens.
Download SKILL.mdSave it as
.claude/skills/ai-prompt-regression-testing/SKILL.md (or your agent's skills folder).- name
- ai-prompt-regression-testing
- description
- Prompt engineering regression test matrix register: baseline outputs, semantic drift thresholds, judge evaluations, and golden dataset.
- category
- engineering
- risk
- safe
- source
- self
- source_type
- self
- date_added
- 2026-10-01
- author
- Ranjeet2063
- tags
- ai, prompt-engineering, testing, evaluation, llm, benchmarking
- source_repo
- Ranjeet2063/agentic-awesome-skills
AI Prompt Regression Test Matrix
What it is: Tracks regression baselines, evaluation rubrics, and automated judge verdicts to prevent output degradation across prompt revisions.
Overview
Provides a standardized, auditable framework and data model for AI Prompt Regression Test Matrix operations across distributed engineering and decentralized application systems.
When to Use This Skill
- When formalizing architectural contracts, security invariants, or operational limits for AI Prompt Regression Test Matrix.
- When cross-functional review is required between protocol developers, smart contract auditors, and AI engineering agents.
- When generating reproducible CSV, SQL DDL, JSON Schema, and Notion property registers for tracking compliance.
How It Works
- Define the parameters, thresholds, and identity bindings required for the target operational register.
- Select appropriate boundary enforcement values from validated enum select sets.
- Export standardized artifacts (CSV table, SQL DDL, JSON Schema) to integrate into validation CI pipelines.
Field Reference
| # | Field Name | Type | SQL Type | JSON Schema Type | Notion Property Type | Example Value |
|---|---|---|---|---|---|---|
| 1 | Prompt TestCase ID | id | SERIAL PRIMARY KEY | integer | Text | PTEST-001 |
| 2 | Prompt Identifier | text | VARCHAR(64) | string | Text | soroban_code_refactor_v2 |
| 3 | Target LLM Model Family | select | VARCHAR(64) | string | Select | Claude 3.5 Sonnet |
| 4 | Evaluation Metric | select | VARCHAR(64) | string | Select | AST Code Correctness |
| 5 | Semantic Drift Threshold | number | NUMERIC(5,2) | number | Number | 0.05 |
| 6 | Golden Baseline Match % | number | NUMERIC(5,2) | number | Number | 98.50 |
| 7 | Judge Model Evaluator | text | VARCHAR(64) | string | Text | Gemini 1.5 Pro |
| 8 | Zero-Shot Reasoning Verified | select | VARCHAR(16) | string | Select | Yes |
| 9 | Latency Bound Seconds | number | NUMERIC(6,2) | number | Number | 3.20 |
| 10 | Test Suite Verdict | select | VARCHAR(32) | string | Select | Passed |
| 11 | Benchmarking Date | date | DATE | string, format: date | Date | 2026-10-01 |
Select Options
Target LLM Model Family
Claude 3.5 Sonnet | GPT-4o | Gemini 1.5 Pro | DeepSeek CoderEvaluation Metric
AST Code Correctness | Semantic Embedding Cosine | Exact Match | Rubric ScoringZero-Shot Reasoning Verified
Yes | NoTest Suite Verdict
Passed | Degraded | Failed RegressionRelations
Audit Reference-> links to the formal review documentation or test repository.Target Architecture-> links to the deployed contract or autonomous agent runtime component.
Show full SKILL.md (203 more words)Show less
Examples
Prompt
How do I configure and track AI Prompt Regression Test Matrix for our production environment?Recommended Next Step
Generate the unified field schema, SQL DDL migration, and JSON validation schema to register into your system catalog.
Workflow: Define criteria -> Run automated verification -> Record baseline -> Monitor invariants.
Best Practices
- Enforce strict typing on numerical bounds and currency amounts; avoid unstructured free-text fields for critical states.
- Re-run validation test suites on every state-altering commit or parameter change.
- Keep example data synthetic and isolated from production cryptographic keys or private endpoints.
Limitations
- Provides architectural specifications, data models, and verification schemas; does not execute direct transaction signing without authorized external tooling.
- Requires network connectivity and valid RPC credentials when querying on-chain states.
Security & Safety Notes
- All parameters declare
risk: safe. No unauthorized state modification or privileged credential access is performed. - Use synthetic dummy keys and mock addresses in test suites and local verification scripts.
Common Pitfalls
- Problem: Mismatched decimal precision between contract runtime and database register. Solution: Always verify decimals using the explicit field mapping in this reference.
- Problem: Missing authorization checks prior to state update. Solution: Cross-validate against the Security Audit register before deployment.
Related Skills
- @ai-agent-tool-routing - covers tool schema registration and retry policy.
- @cross-chain-relayer-audit - covers message hashes, nonces and quorum proofs.
- @smart-contract-formal-verification - verifies state invariants mathematically.
Reusable Prompt
I want to establish a verified AI Prompt Regression Test Matrix register for our production protocol.
Guide me through the required field parameters and output the corresponding SQL DDL and JSON Schema.© sickn33, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/ai-prompt-regression-testing of sickn33/agentic-awesome-skills.
Open the folder on GitHubat commit b84d35a
Used in 1 other repository
We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
AI Prompt Regression Testing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| AI Prompt Regression Testing this skillsickn33/agentic-awesome-skills | 47k | 1 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Dogfood Exploratory QAvercel-labs/agent-browser | 44k | 8 repos | ~2.7k | Automated safety check: Pass | Apache-2.0 | |
| DeerFlow Smoke Testbytedance/deer-flow | 84k | — | ~2.5k | Automated safety check: Notes | MIT | |
| CodexBar Live QAsteipete/CodexBar | 22k | — | ~1.2k | Automated safety check: Pass | MIT | |
| Diagnose Playwright Failure as Product Bugappsmithorg/appsmith | 41k | — | ~1.5k | Automated safety check: Pass | Apache-2.0 | |
| Acceptance Evidence for Deliverieslobehub/lobehub | 83k | — | ~9.7k | Automated safety check: Pass | Apache-2.0 |
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Related
Works with
Categories
Questions about AI Prompt Regression Testing
What does AI Prompt Regression Testing do?
Prompt engineering regression test matrix register: baseline outputs, semantic drift thresholds, judge evaluations, and golden dataset. AI Prompt Regression Testing is an agent skill from sickn33/agentic-awesome-skills. Prompt engineering regression test matrix register: baseline outputs, semantic drift thresholds, judge evaluations, and golden dataset.
When should I use AI Prompt Regression Testing?
AI Prompt Regression Testing fits situations like: tasks that involve QA and bug reports.
How do I install AI Prompt Regression Testing in Claude Code?
Run `npx skills add sickn33/agentic-awesome-skills --skill ai-prompt-regression-testing -a claude-code`. Or copy the skill folder (skills/ai-prompt-regression-testing in sickn33/agentic-awesome-skills) into .claude/skills/ai-prompt-regression-testing in your project. Claude Code loads it when a task matches its description.
How do I install AI Prompt Regression Testing in Codex?
Run `npx skills add sickn33/agentic-awesome-skills --skill ai-prompt-regression-testing -a codex`. Or copy the skill folder (skills/ai-prompt-regression-testing in sickn33/agentic-awesome-skills) into .agents/skills/ai-prompt-regression-testing in your project. Codex loads it when a task matches its description.
Can I use AI Prompt Regression Testing in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill ai-prompt-regression-testing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai-prompt-regression-testing, .gemini/skills/ai-prompt-regression-testing, .github/skills/ai-prompt-regression-testing and .opencode/skills/ai-prompt-regression-testing in your project.
What does AI Prompt Regression Testing need to run?
Going by SKILL.md and its folder, AI Prompt Regression Testing needs the command-line tools its instructions call (claude and gemini).
Does AI Prompt Regression Testing access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is AI Prompt Regression Testing safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does AI Prompt Regression Testing use?
AI Prompt Regression Testing is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does AI Prompt Regression Testing use?
About 1.3k tokens (SKILL.md is roughly 5.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to AI Prompt Regression Testing?
Skills that share tags, products or a category with AI Prompt Regression Testing: Dogfood Exploratory QA (vercel-labs/agent-browser, 44k stars), DeerFlow Smoke Test (bytedance/deer-flow, 84k stars), CodexBar Live QA (steipete/CodexBar, 22k stars) and Diagnose Playwright Failure as Product Bug (appsmithorg/appsmith, 41k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains AI Prompt Regression Testing?
sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,405 GitHub stars. The repository holds 1,497 skills in this directory. The repository was last updated on October 9, 2026.
Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.