Results for “frontmatter-validation”

Validates custom dotnet new templates for correctness before publishing, catching missing fields, parameter bugs, shortName conflicts, constraint issues, and common authoring mistakes.

Plan structure validation, phase completeness checks, reference integrity verification, and artifact existence confirmation. Provides the structured verification layer ensuring GSD artifacts are well-formed and complete.

Fact-forcing gate that blocks Edit/Write/Bash (including MultiEdit) and demands concrete investigation (importers, data schemas, user instruction) before allowing the action. Measurably improves output quality by +2.25 points vs ungated agents.

Blocks Edit/Write/Bash actions until the agent presents concrete facts about imports, data schemas, and the user's instruction, improving output quality.

Fact-forcing gate that blocks Edit/Write/Bash (including MultiEdit) and demands concrete investigation (importers, data schemas, user instruction) before allowing the action. Measurably improves output quality by +2.25 points vs ungated agents.

Fact-forcing gate that blocks Edit/Write/Bash (including MultiEdit) and demands concrete investigation (importers, data schemas, user instruction) before allowing the action. Measurably improves output quality by +2.25 points vs ungated agents.

VQAv2: Making the V in VQA Matter

Uses mutation testing to systematically identify gaps in test vector coverage for cryptographic algorithms, then generates new test vectors that close those gaps. Measures effectiveness by comparing mutation kill rates before and after.

Chameleon: Mixed-Modal Early-Fusion Foundation Models

Validate financial data quality in market analysis documents before publication, checking price scales, instrument notation, date accuracy, allocation totals, and unit usage.

Enforces a verification gate before any completion claim, requiring fresh command output as evidence.

Verifies data structures, files, YAML blocks, or agent output against their defined schema, producing a pass/fail report with actionable fix instructions.

Enforces running verification commands and confirming output before claiming work is complete, fixed, or passing, ensuring evidence precedes any success claims.

Centralized JSON validation for AGENT_SUCCESS_CRITERIA with defensive parsing and injection attack prevention (CVSS 8.2)

Verification-before-completion discipline ensuring all success criteria are met, tests pass, and reviews complete before declaring work done.

Verify tasks marked [X] in tasks.md are implemented, not phantom completions (marked done but backed by missing or dead code).

Forces AI agents to investigate before editing or running destructive commands, improving code quality by requiring concrete facts like importers, data schemas, and user instructions.

Validate Pleasur.ai Stage 01 blog-keyword candidates with the Business potential, Intent, and Difficulty method using current Ahrefs evidence. Use before AIO vetting and prioritization to reject poor business fits, mismatched search intent, and SERPs the brand cannot realistically win.

Runs bottom-up type-chain validation across database, hooks, and UI layers, then fixes errors at the failing layer for project health checks before large changes.

Imported skill __init__ from anthropic

Multimodal Few-Shot Learning with Frozen Language Models

Validates observable behavior of apps, CLIs, APIs, and generated artifacts against a prewritten contract without inspecting source code.

A validation *boundary* is any point where data crosses from a system you do not

Validate backup integrity through cryptographic hash verification, automated restore testing, corruption detection, and recoverability checks to ensure backups are reliable for disaster recovery and ransomware response scenarios.

This skill should be used when the user asks to "run example" or "test example skill".

Validate whether an OSS tool is worth building through staged namespace, existing-solution, and feasibility review

Map product assumptions by risk, confidence, evidence, and next validation step.

Provides grep-based patterns to verify that code artifacts are real implementations rather than stubs or placeholders, covering React components, API routes, database schemas, and hooks.

Runs before every git commit on heleni-memory. Checks: no credentials in tracked files, no oversized files, valid SKILL.md frontmatter for any new/modified skill. Triggers: "commit", "before push", "validate repo", or auto-runs as a git pre-commit hook.

Runs a two-wave validation pipeline (deterministic checks then rule-based checks) before every git commit, writing a sentinel file that a pre-commit hook enforces. Includes optional quick mode (first wave only) and a fix loop with up to three iterations.

Enforces running verification commands and confirming output before claiming work is complete, fixed, or passing, to prevent false success claims.

QA a completed analysis for methodology, accuracy, and bias before it is shared, shipped, or acted on.

Use before claiming work is complete, fixed, or passing, and before committing or opening a PR - run the actual verification command and read its output before making any success claim.

Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always