fmea-analysis
Conduct FMEA for systematic failure mode identification using AIAG-VDA 7-step methodology. Supports DFMEA, PFMEA, and FMEA-MSR with Action Priority risk assessment.
Lot de plugins · par dunnock
Aperçu
fmea-analysis est un lot de plugins pour les outils de code IA publié par dunnock. Places de marché que nous lisons et qui le référencent : 1 (Community GitHub marketplaces). Nous l'avons vu pour la première fois le 2026-10-15 et n'avons enregistré aucun changement depuis. Selon notre passage sur les places de marché du 2026-10-20.
Ce qu'il demande
- S'installe comme lot de plugins
Aucune des places de marché que nous lisons ne publie ses outils ni les réglages qu'il demande.
Ce qu'il déclare, demande et exécute, en détail
N’installez que des plugins de développeurs en qui vous avez confiance. Nous reprenons ce que publient les places de marché et ne testons pas les plugins.
Fonctionne avec
- Claude Code
D'après les marketplaces qui le listent et le transport MCP qu'il déclare, tels que chaque client les documente. Nous ne testons pas les plugins.
Connecter
Commandes et configurations construites uniquement à partir de ce que déclarent ses places de marché. Nous ne les exécutons pas pour vous et ne testons pas les plugins.
En plugin Claude Code
Construit à partir de ce que déclare Community GitHub marketplaces.
/plugin marketplace add ddunnock/claude-plugins
/plugin install fmea-analysis@ddunnock-claude-pluginsOù il est publié
| Place de marché | Statut | Version | Chiffres | Vérifié | Vu pour la première fois |
|---|---|---|---|---|---|
| Place de marché communautaire ddunnock/claude-plugins (Ouvrir la source sur GitHub) | Référencé | 1.0.1 | Forks (GitHub): 7 Étoiles (GitHub): 14 |
Non marqué |
Chaque chiffre est celui de la place de marché et n'est jamais additionné entre places de marché. Une place de marché qui ne publie pas de chiffre n'en affiche aucun : pas de nombre ne veut pas dire zéro.
Listé dans une place de marché communautaire
| Place de marché | Dépôt | Étoiles (GitHub) |
|---|---|---|
| ddunnock-claude-plugins | ddunnock/claude-plugins | 14 |
Quelles places de marché nous lisons et comment nous les vérifions
Ce qui a changé
- Est devenu un produit que nous suivons
- Community GitHub marketplaces: apparu
Plugins similaires
Produits dont les noms, descriptions, outils et skills sont les plus proches de celui-ci par le sens, sur toutes les places de marché que nous lisons. La proximité n'est classée qu'à l'intérieur de cette liste.
-
Conduct Fault Tree Analysis (FTA) for system failure analysis using Boolean logic gates. Identifies minimal cut sets, single points of failure, and failure probabilities.
-
Conduct rigorous 5 Whys root cause analysis with guided questioning, quality scoring, and professional report generation. Includes validation tests and countermeasure development.
-
fmeca io.github.praxec/fmeca
Deterministic, offline FMECA MCP server: failure modes, criticality matrix, mitigations, readiness
-
Conduct Pareto Analysis (80/20 Rule) to identify vital few causes driving majority of problems. Generates Pareto charts and prioritization reports.
-
Conduct Kepner-Tregoe (KT) PSDM analysis using Situation Appraisal, Problem Analysis (IS/IS NOT), Decision Analysis (MUSTS/WANTS), and Potential Problem Analysis.
-
misakanet io.github.Ikalus1988/misakanet
Failure-memory layer for coding agents: search evidence-rated failure lessons by error text.
-
Identify what to measure, test, or track to de-risk a product or AI idea.
-
Institutional-grade Business Analysis skills for Claude. Methodology-grade outputs grounded in BABOK and real delivery experience. Includes four plugins: Capability Mapping (MECE…
-
Effort estimation for AI coding agents. PERT three-point estimation with METR reliability thresholds, modifier stacks (spec clarity, warm context, agent fit), and wave planning…
-
Generate structured decision-making tools — step-by-step guides, bias checkers, scenario explorers, and interactive dash
Plugins similaires par place de marché
La même question posée à chaque place de marché séparément : y a-t-il là un équivalent de ce plugin ?
Référencé sur Claude Code: claude-plugins-community (5)
-
Institutional-grade Business Analysis skills for Claude. Methodology-grade outputs grounded in BABOK and real delivery experience. Includes four plugins: Capability Mapping (MECE…
-
Effort estimation for AI coding agents. PERT three-point estimation with METR reliability thresholds, modifier stacks (spec clarity, warm context, agent fit), and wave planning…
-
Research sprint orchestrator for Claude Code. Ask a question, get a decision-ready brief — every finding is tracked as a typed claim, adversarially challenged, confidence-graded…
-
A causal inference plugin for AI agents. Describe a problem in plain language and it helps you choose a method, check assumptions, write the analysis in R or Python, and…
-
Three AI agents for supply chain operations — demand exception analysis, supplier risk scoring, and a multi-agent orchestrator for S&OP reviews. This plugin gives supply chain…
Référencé sur Claude Code: claude-plugins-official (5)
-
Analyze business data and build custom Pigment models, metrics, and boards through natural language.
-
Skills for adding DeepEval evaluations, tracing, datasets, Confident AI reports, and iterative improvement loops to AI applications.
-
Enhance code quality and security through PagerDuty risk scoring and incident correlation. Score pre-commit diffs against historical incident data and surface deployment risk…
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
Référencé sur Claude: knowledge-work-plugins (5)
-
AI-first project auditor and re-engineer based on the 9 design principles and 7 design patterns from the TechWolf AI-First Bootcamp
-
Streamline engineering workflows — standups, code review, architecture decisions, incident response, and technical documentation. Works with your existing tools or standalone.
-
Write SQL, explore datasets, and generate insights faster. Build visualizations and dashboards, and turn raw data into clear stories for stakeholders.
-
Write feature specs, plan roadmaps, and synthesize user research faster. Keep stakeholders updated and stay ahead of the competitive landscape.
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
Référencé sur Codex: openai-curated (openai/plugins) (5)
-
Answer product and business questions with data
-
Evaluate Codex skills and plugins from chat with a beginner-friendly start command, local-first reports, token budget explanations, and guided benchmarking.
-
CrowdStrike Falcon Fusion skills for authoring, deploying, and executing Fusion workflows. Includes live action discovery, YAML authoring with schema validation, workflow import…
-
PostHog gives your AI agent direct access to your product analytics, feature flags, experiments, error tracking, surveys, logs, and LLM analytics. Ask questions about your data…
-
Codex Security workflows for security scans, analysis, and investigation.
Référencé sur Community GitHub marketplaces (5)
-
Conduct Fault Tree Analysis (FTA) for system failure analysis using Boolean logic gates. Identifies minimal cut sets, single points of failure, and failure probabilities.
-
Conduct rigorous 5 Whys root cause analysis with guided questioning, quality scoring, and professional report generation. Includes validation tests and countermeasure development.
-
Conduct Pareto Analysis (80/20 Rule) to identify vital few causes driving majority of problems. Generates Pareto charts and prioritization reports.
-
Conduct Kepner-Tregoe (KT) PSDM analysis using Situation Appraisal, Problem Analysis (IS/IS NOT), Decision Analysis (MUSTS/WANTS), and Potential Problem Analysis.
-
misakanet io.github.Ikalus1988/misakanet
Failure-memory layer for coding agents: search evidence-rated failure lessons by error text.
Référencé sur Copilot CLI: github/awesome-copilot (5)
-
Explore grouped customer feedback signals by impact and drill into a theme to guide product next steps.
-
Three-layer verification pipeline for AI output. Extracts claims, finds sources, and flags hallucination risks so humans can verify before acting.
-
A comprehensive collection of specialized agents for software analysis, impact assessment, structural quality advisories, and architectural review using CAST Imaging.
-
A runtime-portable 5-agent quality gate that adjudicates text artifacts before they ship. Five role-conditioned LLM deliberators run a 2-round async protocol with cross-read…
-
CrowdStrike Falcon Fusion skills for authoring, deploying, and executing Fusion workflows. Includes live action discovery, YAML authoring with schema validation, workflow import…
Référencé sur Copilot CLI: github/copilot-plugins (5)
-
Toolkit for building Microsoft 365 Copilot declarative agents — scaffolding, JSON manifest development, and capability configuration.
-
workiq-productivity
WorkIQ productivity skills powered by the local WorkIQ CLI — read-only insights across email, meetings, calendar, Teams, SharePoint, projects, and people.
-
workiq
Query Microsoft 365 data with natural language — emails, meetings, documents, Teams messages, and more.
-
Build and manage Microsoft Dataverse solutions using natural language. Includes table/column creation, solution lifecycle, data operations, and MCP server configuration.
-
Build Power Apps Canvas Apps using the Canvas Authoring MCP server.
Référencé sur Cursor: cursor/plugins (5)
-
Work with PostHog from chat: query product analytics and run SQL, manage feature flags and experiments, triage error tracking issues, and review session replays, surveys, and…
-
Iterative self-referential AI loops using the Ralph Wiggum technique.
-
Track AI visibility, sentiment, and citations.
-
Search company knowledge and draft verified answers.
-
Draw and export hand-drawn diagrams from chat.
Référencé sur Docker MCP Catalog (5)
-
Sequential Thinking (Reference)
Dynamic and reflective problem-solving through thought sequences.
-
Read and score Opik traces, experiments, datasets and prompts from your AI assistant.
-
An MCP server to help make U.S. Government open datasets AI-friendly.
-
Tools to interact with the Camunda 7 Community Edition Engine using the Model Context Protocol (MCP). Whether you're automating workflows, querying process instances, or…
-
Connect your chat repl to wolfram alpha computational intelligence.
Référencé sur Official MCP Registry (5)
-
fmeca io.github.praxec/fmeca
Deterministic, offline FMECA MCP server: failure modes, criticality matrix, mitigations, readiness
-
misakanet io.github.Ikalus1988/misakanet
Failure-memory layer for coding agents: search evidence-rated failure lessons by error text.
-
Industrial glossary, protocol reference, technical search and OEE calculation. Read-only.
-
dxpert.ai — industrial AI-readiness & UNS agents
Industrial AI-readiness diagnostics, UNS design, and UNS agents for MCP clients.
-
Connects AI assistants to QCDatabase.AI for everyday construction quality-control work.
Référencé sur npm registry (MCP servers) (5)
-
easyeda-mcp-pro io.github.oaslananka/easyeda-mcp-pro
MCP server for EasyEDA Pro: PCB inspection, BOM, exports, and hardware review.
-
dealflowpro io.github.jbechtel-97/dealflowpro
Multifamily real estate deal analysis — cap rate, DSCR, IRR, DFP Score, max offer price
-
CVE, KEV, EPSS, SBOM and advisory lookups; per-CVE exposure from Shodan data (© Shodan). Keyless.
-
One workspace for every AI coding assistant. Shared tasks, memory, and governance.
-
Local persistent memory and Markdown wiki for AI coding agents: 24 MCP tools, no gateway required.
Trouvés par le sens, et non par un code ou un dépôt commun : les plugins similaires restent des produits distincts, et ceci n'est ni un avis ni une recommandation.
Vous voulez cette marque pour votre plugin dans notre catalogue ?
Prouvez que vous le maintenez avec un fichier dans son dépôt, un fichier sur votre domaine ou un enregistrement DNS, et vous pourrez afficher cette marque sur la fiche, avec des bannières à jour pour votre site et votre README. Comment se passe la vérification
Vous recevez aussi des alertes quand une marketplace le publie, le retire, change sa marque vérifiée ou ce qu'il demande, et son endpoint distant est surveillé comme un service web.
Données issues de Community GitHub marketplaces. Les chiffres proviennent de nos propres passages réguliers sur les places de marché, dernière lecture le . Nous ne publions aucune coordonnée des éditeurs de plugins.