LLM Mart Basic
@llm-mart · Joined Jun 2026
Use this skill when a Salesforce matter must be assigned a standardized matter type, risk tier, or escalation gate before routing or handoff. Defines all matter types (org-config, automation, code, integration, security/IAM, data, sales/CPQ, service/SLA, experience-cloud, marketi
Use this skill when a Salesforce matter must be classified and routed to the right specialist agent, when a matter crosses multiple Salesforce domains and needs parallel review, or when specialist agents disagree and the conflict must be resolved. It defines routing rules per mat
Use this skill to statically review AI/BI Genie agent and dashboard design: agent scoping (30-table limit), instructions and trusted assets, metric-view correctness, dashboard limits and rendering, benchmark design and honest accuracy reading, and the critical 'Individual data' v
Use this skill to review Databricks data protection and privacy design for regulatory alignment and least-privilege enforcement: row filters and column masks, ABAC policies, data classification, deletion and GDPR erasure mechanics, Delta Sharing egress, residency and Geo constrai
Use this skill to design and verify data quality expectations, table constraints, Lakehouse Monitoring, freshness detection, event-log interrogation, quality SLAs, and downstream quality signaling for Lakeflow pipelines. Reads pipeline source, table schema, expectations, monitor
Use this skill to review a Declarative Automation Bundle configuration, authentication setup, and deployment flow against production readiness criteria: bundle structure, deployment modes, run-as identity boundaries, variable resolution timing, OAuth and environment-variable auth
Use this skill to statically review Databricks cost and cost-attribution: system.billing.usage and system.billing.list_prices for correct joins, custom-tag-based attribution with coverage-confidence reporting, DBU uptime charging semantics, serverless versus classic cost comparis
Use this skill to review generative-AI agent design on Databricks: Mosaic AI Agent Framework and ResponsesAgent interface, Databricks AI Search index variant and sync-mode choice, retrieval and context engineering, MCP server category and trust boundaries, external model-provider
Use this skill to review generative-AI evaluation, tracing, and observability design on Databricks: MLflow Tracing instrumentation and span design, trace storage and governance, `mlflow.genai.evaluate()` harness design, the judge-versus-scorer distinction, built-in judge selectio
Use this skill to review Databricks identity and network security design for proper admin separation, SCIM/federation configuration, credential hygiene, and network boundary enforcement: admin roles, service-principal posture, OAuth vs PAT, token lifecycle, IP access lists, serve
Use this skill to design Lakeflow Spark Declarative Pipelines: medallion layering, Lakeflow Jobs orchestration and task dependencies, Delta table layout (liquid clustering, deletion vectors, Predictive Optimization), Auto Loader ingestion, schema evolution and `_rescued_data`, ma
Review and guide Databricks Lakehouse engineering on Azure: medallion architecture (bronze/silver/gold), Delta Lake pipelines, ADLS Gen2 access via Unity Catalog external locations and storage credentials, Access Connector managed identity, cluster access mode enforcement, AKV-ba
Mutating-runtime live guard for Unity Catalog privilege management on Azure Databricks. Executes exactly ONE GRANT or REVOKE of a single privilege on a single Unity Catalog securable (schema, table, or volume) to a single principal — with explicit written human approval, dry-run
Use this skill to classify an incoming Databricks task and route it to the narrowest owning specialist on the Databricks board. Classifies on intent, business context, artifact type, blast radius, required evidence, implied runtime authority, and specialist ownership; emits a sin
Use this skill to review machine-learning model lifecycle on Databricks: MLflow 3 with Unity Catalog as default registry, alias-based promotion and champion/challenger patterns, feature-store design with point-in-time correctness, Model Serving endpoint configuration and traffic
Use this skill to review Databricks account and workspace topology for scalability and Well-Architected alignment: metastore-per-region constraint, workspace segmentation ratios, serverless vs classic placement, catalog organisation, cross-region and cross-organisation access pat
Use this skill to diagnose and design platform reliability using system-table evidence, job and pipeline execution review, cluster policies, instance pools, quota headroom, and disaster-recovery posture: job timeouts and retries, run-history retention, managed DR design, incident
Use this skill to statically review SQL warehouse and query performance: warehouse type and sizing for concurrency, Photon and Predictive I/O applicability, three-tier caching semantics and when a cached result is misleading, query-profile reading for skew and spill, data layout
Use this skill to verify Structured Streaming query correctness and recovery: state-schema immutability, checkpoint compatibility across restarts, watermark semantics, trigger selection (AvailableNow, Once, ProcessingTime), exactly-once vs at-least-once sinks, foreachBatch idempo
Use this skill to review Unity Catalog governance design for privilege correctness, ownership clarity, and least-privilege enforcement: three-level namespace design, GRANT inheritance, ownership, workspace-catalog binding, governed tags, storage credentials, and audit completenes
Fourteen posts of being wrong in production, compressed to checkboxes
Healthy nodes, a quiet network, 300 restarts in three days, and a latency budget measured in milliseconds
Discovery worked. Ping worked. Every TCP connection timed out, and later the tunnel only worked when someone had a terminal open.
Every VM came back. The cluster did not. Declarative systems converge on config, and the datapath isn't config.
A surprising share of AI-in-the-terminal failures aren't the AI. They're zsh, and a version of bash from 2006.
A Claude Code plugin turns standalone project configuration into a namespaced, installable extension that teams and communities can update as one unit.
None of the safety came from the model. It came from six boring habits.
Skills package instructions and references. Subagents run work in a separate context and return results. They solve different problems and can be composed deliberately.
Six hours in, one step left, everything green, and the incident that didn't happen
CLAUDE.md carries persistent project context. Skills load reusable procedures when relevant. Separating stable facts from task-specific workflows keeps both easier to maintain.
Twenty minutes recovering secrets that never existed, and the one sentence from a human that ended it
An API request routing a model's tool call through an approval gate to a remote MCP server
31 config keys, two audits, and why the first one was wrong in both directions
The official MCP Registry stores standardized server metadata rather than package code. Publishers verify a namespace, describe installation or remote access, and submit immutable versions.
Everyone looks at the Dockerfile. The file that actually leaked the key was the project file.
Remote MCP authorization uses established OAuth standards, but secure integration still requires issuer validation, least-privilege scopes, protected token handling, and server-side enforcement.
"Copy it over and switch the reference" is two steps, and the outage lives in the one nobody checks
stdio fits local processes and prototypes. Streamable HTTP fits hosted services and shared integrations. The right choice follows where the capability runs and who must reach it.
The most important rule wasn't about what I could change. It was about what I was allowed to display.
Tools perform operations, resources expose readable context, and prompts provide reusable templates. Choosing the correct primitive makes an MCP server easier to understand and govern.
/plugin-review
plugin-review
"Tiered plugin quality review: branch (quick gates),
/promote-discussions
promote-discussions
Check GitHub Discussions for highly voted learnings and promote them to Issues.
/rules-eval
rules-eval
Evaluate Claude Code rules in .claude/rules/ directories for quality
/skills-eval
skills-eval
Audit skill quality, frontmatter compliance, token efficiency, and activation reliability. Recommends improvements.
/test-skill
test-skill
Test Claude Code skills using RED/GREEN/REFACTOR TDD phases in fresh subagents to prevent priming bias.
/validate-hook
validate-hook
Validate hooks for security, performance, and SDK compliance
/validate-plugin
validate-plugin
Validate plugin structure, schema, and naming. Use for plugin creation, debugging, or verification.
/arch-init
arch-init
Initialize projects with architecture-aware templates using paradigm research and selection guidance for the target domain.
/blueprint
blueprint
Generate an implementation plan with system architecture design and dependency-ordered task breakdown from a specification.
/brainstorm
brainstorm
Guide project ideation through Socratic questioning to generate briefs with validated approaches and decision rationale.
/execute
execute
Execute implementation plan systematically with progress tracking and checkpoint validation
/mission
mission
Run full attune lifecycle as a mission with state detection and phase routing
/project-init
project-init
Initialize a new project with git setup, CI/CD workflows, pre-commit hooks, Makefiles, and language-specific tooling.
/skill-library
skill-library
Build a project skill library under .claude/skills/ as a resumable mission: discover, author in parallel, review adversarially.
/specify
specify
Create specs from project briefs with acceptance criteria and testable requirements
/upgrade-project
upgrade-project
Update existing project configurations to current best practices with selective component upgrades
/validate
validate
Validate project structure and configurations against best practices with detailed issue reporting
/war-room
war-room
Convene a multi-LLM expert panel to pressure-test strategic decisions with adversarial review and reversibility assessment.
/visualize
visualize
Generate visual diagrams of codebase structure using Mermaid Chart MCP rendering.
/ai-hygiene-audit
ai-hygiene-audit
Audit codebase for AI-generated code quality issues (vibe coding, Tab bloat, slop)
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21 views 0 likesPi — A cross-platform AI coding agent, bringing the Claude Code experience to your desktop. No environment setup, no terminal commands. Download and start codin…
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13 views 0 likesA telegram bot for searching and auto-saving.
13 views 0 likes金蝶云星空 K3Cloud MCP Server,让 AI 助手(Claude Desktop、Claude Code、Cursor、Cline、Cherry Studio、Openclaw 等任意支持 MCP 协议的客户端)通过自然语言查询和操作金蝶 ERP 系统。
19 views 0 likesRewrite frontier research using allegorical structural mapping.
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11 views 0 likesGive any AI agent a full desktop — it sees the screen, clicks, types, and runs apps like a human. Automate anything with a UI: browsers, legacy software, intern…
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12 views 0 likesOpen-source, self-hosted customer support desk in a single binary. A lightweight alternative to Intercom, Zendesk, Chatwoot.
13 views 0 likes54 rigorous skills for Codex, OpenCode, and Pi: code review, security audit, feature development, frontend design, MCP tools, Hugging Face ML/training, and more…
18 views 0 likesA wonderful list of Game Development resources.
11 views 0 likesOpen Science Desktop — local-first, model-agnostic AI research workbench for macOS, Windows & Linux. Open-source Claude Science desktop alternative built on Tau…
11 views 0 likesLexora — Personal AI workspace built around Desktop / 以 Desktop 为核心的个人 AI 工作台
11 views 0 likesOpen-source, AI-native Evernote alternative with native MCP. Zero-cost on Cloudflare or self-hosted with Docker.
11 views 0 likesFull job-hunt Claude skill bundle — Job Description decoder + Resume builder (11 templates) + Behavioral Interview / story bank. Three self-contained sub-skills…
11 views 0 likes