Agent skill

Validator Expert

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Validate production readiness of Vertex AI Agent Engine deployments across security, monitoring, performance, compliance, and best practices.

MITAuto-check passedDevOps & Cloud

Install Validator Expert

skills CLI

$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill validator-expert -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install jeremylongshore/tons-of-skills-marketplace validator-expert --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/validator-expert .claude/skills/validator-expert && rm -rf skills-src

Use ~/.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/

Paste into Claude Code

Install the "validator-expert" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/validator-expert into .claude/skills/validator-expert/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "validator-expert", 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

$skill-installer install https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/validator-expert

Type 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.

skills CLI

$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill validator-expert -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install jeremylongshore/tons-of-skills-marketplace validator-expert --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/.curated/validator-expert .agents/skills/validator-expert && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "validator-expert" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/validator-expert into .agents/skills/validator-expert/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "validator-expert", 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.

skills CLI

$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill validator-expert -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install jeremylongshore/tons-of-skills-marketplace validator-expert --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/.curated/validator-expert .cursor/skills/validator-expert && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "validator-expert" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/validator-expert into .cursor/skills/validator-expert/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "validator-expert", 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

$ gemini skills install https://github.com/jeremylongshore/tons-of-skills-marketplace.git --path skills/.curated/validator-expert

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill validator-expert -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install jeremylongshore/tons-of-skills-marketplace validator-expert --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/.curated/validator-expert .gemini/skills/validator-expert && rm -rf skills-src

Use ~/.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/

Paste into Gemini CLI

Install the "validator-expert" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/validator-expert into .gemini/skills/validator-expert/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "validator-expert", 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.

GitHub CLI

$ gh skill install jeremylongshore/tons-of-skills-marketplace validator-expert

Installs 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).

skills CLI

$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill validator-expert -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/.curated/validator-expert .github/skills/validator-expert && rm -rf skills-src

Use ~/.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/

Paste into GitHub Copilot

Install the "validator-expert" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/validator-expert into .github/skills/validator-expert/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "validator-expert", 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.

skills CLI

$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill validator-expert -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install jeremylongshore/tons-of-skills-marketplace validator-expert --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/.curated/validator-expert .opencode/skills/validator-expert && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "validator-expert" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/validator-expert into .opencode/skills/validator-expert/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "validator-expert", 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: validator-expert
GitHub stars: 2.8k
Token cost: ~1.9k tokens
SKILL.md length: 722 words
Files: 7 (incl. scripts, references)
Skills in repo: 3,342
Repo updated: Oct 10, 2026
First seen: Oct 8, 2026
Licence: MIT

At a glance

Validate production readiness of Vertex AI Agent Engine deployments across security, monitoring, performance, compliance, and best practices.

Works in 7 steps: Retrieve the deployment configuration… → Run the security validation suite (see… → Run the monitoring validation suite → …
Asked to validate a deployment
SKILL.md covers Current State, Overview, Prerequisites and Instructions, plus 4 more sections
Runs Shell scripts from its folder; calls gcloud

What it does

Validator Expert is an agent skill from jeremylongshore/tons-of-skills-marketplace. Validate production readiness of Vertex AI Agent Engine deployments across security, monitoring, performance, compliance, and best practices. Generates weighted scores (0-100%) with actionable remediation plans. Use when asked to validate a deployment, run a production readiness check, audit security posture, or verify compliance for Vertex AI agents. Trigger with "validate deployment", "production readiness", "security audit", "compliance check", "is this agent ready for prod", "check my ADK agent", "review…

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts and reference files (for example `ARD.md`, `PRD.md` and `references/monitoring-checklist.md`). Compatibility notes: Designed for Claude Code

It sits in DevOps & Cloud, covering Deployment, Security review and Regulatory compliance. It works with Vertex AI and Google Cloud. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

Asked to validate a deployment
Run a production readiness check
Audit security posture
Verify compliance for Vertex AI agents

Example prompts

“validate deployment”
“production readiness”
“security audit”
“/validator-expert”

Requirements

Python 3
A Bash shell
Compatibility (from SKILL.md): Designed for Claude Code
Pre-approved tools (allowed-tools): Read, Grep, Glob, Bash(gcloud:*), Bash(python:*), Bash(pylint:*), Bash(flake8:*), Bash(mypy:*), Bash(bandit:*), Bash(pytest:*)

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

Retrieve the deployment configuration using the Python SDK (vertexai.Client().agent_engines.get(name)) or REST API (GET…
Run the security validation suite (see security checklist)
Run the monitoring validation suite
Run the performance validation suite
Run the compliance validation suite
Calculate weighted scores per category and compute the overall production readiness percentage
Generate a prioritized recommendation list sorted by score impact per remediation effort

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
- Read
- Grep
- Glob
- Bash(gcloud:*)
- Bash(python:*)
- Bash(pylint:*)
- Bash(flake8:*)
- Bash(mypy:*)
- Bash(bandit:*)
- Bash(pytest:*)
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Shell), which the agent can run.
Shell commands in SKILL.md call:
- gcloud
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
- cloud.google.com
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.
Compatibility
Designed for Claude Code
From compatibility in the SKILL.md frontmatter.

Context cost

Validator Expert loads about 1.9k tokens when it runs, and up to ~5.7k if it reads all its reference files. Until then it costs about 164 tokens; SKILL.md has 722 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~164
When it runs · the whole SKILL.md, loaded when a task matches: ~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~5.7k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 722 words, ~1,859 tokens.

Download SKILL.mdSave it as .claude/skills/validator-expert/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.

name: validator-expert
description: Validate production readiness of Vertex AI Agent Engine deployments across security, monitoring, performance, compliance, and best practices. Generates weighted scores (0-100%) with actionable remediation plans. Use when asked to validate a deployment, run a production readiness check, audit security posture, or verify compliance for Vertex AI agents. Trigger with "validate deployment", "production readiness", "security audit", "compliance check", "is this agent ready for prod", "check my ADK agent", "review before deploy", or "production readiness check". Make sure to use this skill whenever validating ADK agents for Agent Engine.
allowed-tools: Read, Grep, Glob, Bash(gcloud:*), Bash(python:*), Bash(pylint:*), Bash(flake8:*), Bash(mypy:*), Bash(bandit:*), Bash(pytest:*)
compatibility: Designed for Claude Code
version: 2.22.0
author: Jeremy Longshore <jeremy@intentsolutions.io>
license: MIT
tags: vertex-ai, security, compliance, validation, production-readiness, gcp
model: inherit
effort: high
argument-hint: [project-id]

Validator Expert

Current State

!gcloud config get-value project 2>/dev/null || echo 'no active project' !gcloud auth list --filter=status:ACTIVE --format="value(account)" 2>/dev/null || echo 'not authenticated'

Overview

Validate production readiness of Vertex AI Agent Engine deployments by executing weighted checks across five categories: security (30 points), monitoring (20 points), performance (25 points), compliance (15 points), and best practices (10 points). This skill produces a 0-100% composite score with pass/fail per check and prioritized remediation recommendations.

Prerequisites

gcloud CLI authenticated with roles/aiplatform.viewer, roles/iam.securityReviewer, and roles/monitoring.viewer
Access to the target Google Cloud project and Vertex AI Agent Engine deployment
Cloud Monitoring API and Cloud Logging API enabled in the project
Knowledge of the deployment's expected SLOs (latency targets, error rate thresholds)
Read-only access to IAM policies, VPC-SC configurations, and service account bindings

Instructions

Retrieve the deployment configuration using the Python SDK (vertexai.Client().agent_engines.get(name)) or REST API (GET https://{LOCATION}-aiplatform.googleapis.com/v1/projects/{PROJECT}/locations/{LOCATION}/reasoningEngines/{ID}) and parse model, scaling, and feature settings
Run the security validation suite (see security checklist):
- Check if Agent Identity is enabled (recommended over service accounts for 2025+ deployments)
- If using service accounts, verify IAM roles follow least-privilege (roles/aiplatform.expressUser, not roles/aiplatform.admin)
- Confirm VPC Service Controls perimeter is active and correctly scoped
- Check encryption at rest (CMEK or Google-managed) and in-transit (TLS 1.3)
- Scan configuration files and environment variables for hardcoded secrets
- Validate Model Armor is enabled with roles/modelarmor.user granted
- Check Memory Bank IAM Conditions for multi-tenant agents
Run the monitoring validation suite:
- Verify Cloud Monitoring dashboards exist with required panels (request count, error rate, latency)
- Confirm alerting policies cover error rate spikes, latency SLO breaches, and cost thresholds
- Check token usage tracking is enabled with per-model granularity
- Validate structured logging with severity levels and correlation IDs
- Confirm latency SLOs are defined with p95 and p99 targets
Run the performance validation suite:
- Verify auto-scaling is configured with appropriate min/max instance counts
- Check resource limits (CPU, memory) match expected workload profile
- Confirm caching strategy is implemented for repeated prompts or embeddings
- Validate Code Execution Sandbox TTL is set between 7-14 days
- Check Memory Bank retention policy (min 100 memories, auto-cleanup enabled)
Run the compliance validation suite:
- Confirm audit logging is enabled for all admin and data access operations
- Verify data residency meets regional requirements
- Check privacy policies and data retention schedules
- Validate backup and disaster recovery configuration
Calculate weighted scores per category and compute the overall production readiness percentage
Generate a prioritized recommendation list sorted by score impact per remediation effort

Show full SKILL.md (316 more words)Show less

Output

Production readiness score: 0-100% with status (READY >= 85%, NEEDS WORK 70-84%, NOT READY < 70%)
Per-category breakdown: security (x/30), monitoring (x/20), performance (x/25), compliance (x/15), best practices (x/10)
Pass/fail table for each individual check with evidence notes
Prioritized remediation plan: action items ranked by score improvement per effort
Comparison to previous validation run (if available) showing score delta

Error Handling

Error	Cause	Solution
Insufficient IAM permissions	Viewer roles not granted on target project	Request `roles/aiplatform.viewer` and `roles/iam.securityReviewer` from project admin
Agent deployment not found	Incorrect agent ID or deployment deleted	Verify agent ID with `vertexai.Client().agent_engines.list()` or REST `GET .../reasoningEngines`; confirm deployment region
Monitoring API returns no data	API not enabled or agent has zero traffic	Enable Monitoring API; generate synthetic traffic to populate baseline metrics
VPC-SC configuration inaccessible	Organization policy restricts VPC-SC reads	Request `roles/accesscontextmanager.policyReader` at organization level
Compliance check inconclusive	Audit logs not enabled or retention too short	Enable Data Access audit logs; set log retention to minimum 365 days

Examples

Scenario 1: Pre-Launch Validation -- Validate a new ADK agent before production launch. Run all five validation categories. Target score: 85%+ overall, with security score at 28/30 minimum. Generate remediation plan for any failing checks.

Scenario 2: Post-Incident Security Audit -- After a permission escalation incident, re-validate security posture. Focus on IAM least-privilege, service account bindings, and VPC-SC perimeter integrity. Compare scores against the last passing validation.

Scenario 3: Quarterly Compliance Review -- Execute compliance and monitoring validation suites for SOC 2 audit preparation. Verify audit logging coverage, data residency compliance, and backup/DR configuration. Export results as evidence artifacts.

Resources

Validation checklists (read the relevant one during each validation step):

Security checklist — IAM, VPC-SC, encryption, Model Armor (30% weight)
Monitoring checklist — dashboards, alerts, SLOs, logging (20% weight)
Performance & compliance checklist — auto-scaling, caching, audit logs, DR (40% weight)

Official Google Cloud documentation:

Vertex AI Security Best Practices
Cloud Monitoring Alerting
VPC Service Controls
Model Armor
Cloud Audit Logs

Files

SKILL.md and 6 other files (scripts, references) in skills/.curated/validator-expert of jeremylongshore/tons-of-skills-marketplace.

SKILL.md
ARD.md
PRD.md
references/monitoring-checklist.md
references/performance-compliance-checklist.md
references/security-checklist.md
scripts/validate-production.sh

Open the folder on GitHubat commit cfae287

Compare with similar skills

Validator Expert 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.

Validator Expert compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Validator Expert this skilljeremylongshore/tons-of-skills-marketplace	2.8k	—	~1.9k	Automated safety check: Pass	MIT	today
Google Agents CLI Scaffoldpifferologo/cloud-agents-cli	129	1 repos	~2.9k	Automated safety check: Notes	Apache-2.0	1 mo ago
Batfish Config Analysisautomateyournetwork/netclaw	676	—	~1.4k	Automated safety check: Pass	Apache-2.0	today
Frontmcp Production Readinessagentfront/frontmcp	146	—	~6.5k	Automated safety check: Pass	Apache-2.0	today
AWS Cloudformationaws/agent-toolkit-for-aws	2.8k	—	~3.6k	Automated safety check: Pass	Apache-2.0	today
Senior DevOps Toolkitmaslennikov-ig/claude-code-orchestrator-kit	260	6 repos	~1.1k	Automated safety check: Notes	Custom licence	7 mo ago

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Questions about Validator Expert

What does Validator Expert do?

Validate production readiness of Vertex AI Agent Engine deployments across security, monitoring, performance, compliance, and best practices. Validator Expert is an agent skill from jeremylongshore/tons-of-skills-marketplace. Validate production readiness of Vertex AI Agent Engine deployments across security, monitoring, performance, compliance, and best practices.

When should I use Validator Expert?

Validator Expert fits situations like: asked to validate a deployment; run a production readiness check; audit security posture; verify compliance for Vertex AI agents.

How do I install Validator Expert in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill validator-expert -a claude-code`. Or copy the skill folder (skills/.curated/validator-expert in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/validator-expert in your project. Claude Code loads it when a task matches its description.

How do I install Validator Expert in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill validator-expert -a codex`. Or copy the skill folder (skills/.curated/validator-expert in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/validator-expert in your project. Codex loads it when a task matches its description.

Can I use Validator Expert 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 jeremylongshore/tons-of-skills-marketplace --skill validator-expert -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/validator-expert, .gemini/skills/validator-expert, .github/skills/validator-expert and .opencode/skills/validator-expert in your project.

What does Validator Expert need to run?

Going by SKILL.md and its folder, Validator Expert needs a shell for the scripts in its folder and the command-line tools its instructions call (gcloud). Our summary lists: Python 3; A Bash shell. Its frontmatter pre-approves these tools: Read, Grep, Glob, Bash(gcloud:*), Bash(python:*), Bash(pylint:*), Bash(flake8:*), Bash(mypy:*), Bash(bandit:*), Bash(pytest:*). Compatibility (from SKILL.md): Designed for Claude Code.

Does Validator Expert access the network?

SKILL.md names 1 domain. As links in the text: cloud.google.com. This is read from the text; nothing was executed.

Is Validator Expert 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Validator Expert use?

Validator Expert is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Validator Expert use?

About 1.9k tokens (SKILL.md is roughly 7.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.8k tokens, read only when the agent opens those files.

What are the alternatives to Validator Expert?

Skills that share tags, products or a category with Validator Expert: Google Agents CLI Scaffold (pifferologo/cloud-agents-cli, 129 stars), Batfish Config Analysis (automateyournetwork/netclaw, 676 stars), Frontmcp Production Readiness (agentfront/frontmcp, 146 stars) and AWS Cloudformation (aws/agent-toolkit-for-aws, 2.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Validator Expert?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Validator Expert

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Compatibility

Context cost

Safety

SKILL.md

Validator Expert

Current State

Overview

Prerequisites

Instructions

Output

Error Handling

Examples

Resources

Files

Compare with similar skills

Similar skills

More from jeremylongshore/tons-of-skills-marketplace

Related

Questions about Validator Expert