validate

validate is a skill for Claude Code from myclaude-sh/myclaude-creator-engine. It costs 60 tokens per session (4,103 once invoked), scanned A, original, MIT.

A quality checker for products stored in a workspace. It uses three levels of review covering structure, quality, distinctiveness, and deeper issues.

In plain words
What is it for?
Use it after creating or changing a product, before publishing, or when you need a quality report. It is limited to products in the workspace.
Why use it?
It shows whether a product is ready to publish and gives instructions for fixing problems it finds.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: mentions subagents; names the NotebookEdit tool.

Part of the studio-engine-core plugin — 8 skills shipped together

Good fit Use it after creating or changing a product, before publishing, or when you need a quality report. It is limited to products in the workspace.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/myclaude-sh/myclaude-creator-engine/validate
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add myclaude-sh/myclaude-creator-engine --skill validate
Clone the repo
git clone --depth 1 https://github.com/myclaude-sh/myclaude-creator-engine

Made for: Claude Code.

Or install studio-engine-core, the plugin that ships this one along with the rest of its 8 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for validate

README.md
[![agentmods](https://agentmods.dev/badge/skills/myclaude-sh/myclaude-creator-engine/validate/github.svg)](https://agentmods.dev/skills/myclaude-sh/myclaude-creator-engine/validate)
Your own site
<a href="https://agentmods.dev/skills/myclaude-sh/myclaude-creator-engine/validate"><img src="https://agentmods.dev/badge/skills/myclaude-sh/myclaude-creator-engine/validate/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for validate

Your own site · 80×15
<a href="https://agentmods.dev/skills/myclaude-sh/myclaude-creator-engine/validate"><img src="https://agentmods.dev/badge/skills/myclaude-sh/myclaude-creator-engine/validate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 60 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,103 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00060 $0.04103
Opus 5 $0.00030 $0.02051
Sonnet 5 $0.00012 $0.00821
Haiku 4.5 $0.00006 $0.00410

Measured 9d ago against content hash 6c9a986c8818, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

validate scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/validate/SKILL.md · 212 lines

How it starts

The opening of the file, as written. The whole thing — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Validator

Run MCS quality checks on any product in workspace/ and return actionable, scored reports.

When to use: After building or modifying a product, before publishing, or anytime you want a quality snapshot.

When NOT to use: On products outside workspace/. Do not use to validate the Engine itself.


Activation Protocol

  1. Shared preamble: Load references/quality/activation-preamble.md — context assembly, persona adaptation, deterministic routing rules.
  2. Detect product type: read .meta.yamlproduct.type and state.phase
    • Missing → infer from file structure (SKILL.md, AGENT.md, SQUAD.md, hooks.json, etc.)
    • Cannot determine → ask: "What product type is this?" 1b. Mode selection (Express vs Guided). Read creator.yaml → preferences.workflow_style. Resolve the flow mode:
    • --express flag OR workflow_style == "autonomous"Express mode. Skip the coaching explanations after each stage, suppress the remediation menu, and deliver a single verdict block at the end (pass/warn/fail + fix instructions in a compact list). Persona tone still holds; only the conversational scaffolding is trimmed.
    • workflow_style == "guided" or missing → Guided mode (default). Walk each stage with the full coaching voice and propose remediation interactively after failing stages.
  3. Maintain creator persona: Read creator.yaml → adapt to profile.type and technical_level
  4. Load voice identity: Load references/quality/engine-voice-core.md. Load the full references/quality/engine-voice.md only for peak moments (first-pass milestone celebration, confronting failure verdict) — see UX Stack below. 3b. Exemplar load: Load references/quality/exemplar-outputs.md sections E6 and E7 only — the validation pass and failure exemplars. Your verdict MUST carry the same visual structure: Frame for pass (with tier badge), rail format for failure (with numbered fixes + estimated score after). Adapt to creator context — never copy verbatim.
  5. Load DNA requirements: product-dna/{type}.yaml 4b. Load architectural DNA: Read structural-dna.md. The 10 architectural principles and the Tier 1 DNA patterns (D1-D4, D13, D14) are the canonical audit baseline — Stages 3 and 5 grep the product against them, and any violation surfaces as coaching.
  6. Load product spec: references/product-specs/{type}-spec.md 5b. Load entity ontology (squad/system/agent/workflow/minds): If type ∈ {squad, system, agent, minds, workflow}, read references/entity-ontology.md. This substrate drives semantic validation:
    • §HERITAGE: verify the product inherits correct DNA from its lineage (squad must pass all agent DNA + D9/D10/D12/D18)
    • §COMPOSITION: verify only allowed compositions (squad→agents+minds+skills+workflows; system→everything; workflow→skills only)
    • §AGENT_ROLES: if .meta.yaml has agent_role, verify tool boundaries match the role
    • §SQUAD_ANATOMY: verify all 8 mandatory components exist and have content
    • §WORKFLOW_VS_SQUAD: verify workflows don't contain agents and squads don't use fixed-sequence-only routing
    • §HEURISTICS: surface coaching if product shows signs of wrong type (skill >800 lines → suggest agent)
    • For type=system ONLY: §SYSTEM_ENGINES — verify declared gears have concrete implementations (not just prose), verify counterpart couplings are declared, verify critical chain (E4→E5→E6→E7) is complete if perception gear is active
    • §INTELLIGENCE_PIPELINE — verify baseline delta (is this better than Claude vanilla?), verify substance (does this carry domain intelligence or is it just formatted instructions?)
  7. Load config: config.yaml → scoring weights, thresholds, placeholder patterns
  8. Load gates: quality-gates.yaml → state transition rules 7b. Load proactives: Load references/engine-proactive.md — wire #1 (pipeline guidance: after validate passes, guide to /test then /package), #19 (error recovery: on validation failure, propose specific fixes), #20 (test mandate: if MCS-2+ and not tested, block /package suggestion).
  9. CLI contract: Load references/cli-contract.md for Stage 6 (CLI Preflight). Severity map:
    • Warning: validate --json — CLI validation is advisory during /validate (blocking only during /publish)
    • Warning: doctor --json — health check is advisory, score < 8.0 triggers suggestion
    • Stage 6 detail protocol: references/validation-stages/stage-6-cli-preflight.md

Read the full file on GitHub · 212 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 212 lines · 60 tokens per session scan A 6c9a986c8818

Subscribe to this mod's changes

validate is a skill published in the GitHub repository myclaude-sh/myclaude-creator-engine (25 stars, last pushed 5mo ago), licensed MIT. It adds 60 tokens to every session and 4,103 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

thinking-theory-of-constraints

When throughput or latency is pipeline-limited, identify the single binding constraint and exploit, subordinate, elevate, then recheck—ignore non-constraints.

tjboudreaux/cc-thinking-skills · 37 tokens

Vizra ADK Memory System

Implement persistent memory, session context, and vector memory (RAG) for AI agents.

vizra-ai/vizra-adk · 24 tokens

foundation-models

On-device LLM integration using Apple's Foundation Models framework. Use when implementing AI text generation, structured output, or tool calling.

rshankras/claude-code-apple-skills · 29 tokens

analytics-interpretation

Interpret app metrics and make data-driven decisions. Covers DAU/MAU, retention, LTV, ARPU, App Store Connect analytics, AARRR funnel analysis, cohort analysis, and diagnostic decision trees. Use when user wants to understand their metrics, diagnose problems, or build a data-driven growth plan.

rshankras/claude-code-apple-skills · 68 tokens

app-namer

Turn an app idea into validated, App-Store-ready name candidates. Use when the user says "name my app", "what should I call it", "app name ideas", "help me name this app", "is this name available", or needs to pick a brandable, ownable name before reserving it in App Store Connect.

rshankras/claude-code-apple-skills · 73 tokens

in-app-events

Generates In-App Event metadata templates for App Store Connect — event names, descriptions, badge types, image specs, and deep link configuration. Use when creating events for App Store visibility, engagement campaigns, or seasonal promotions.

rshankras/claude-code-apple-skills · 48 tokens