LLM Mart Basic
@llm-mart · Joined Jun 2026
Design, review, and improve AWS DevOps Agent-compatible skills, investigation workflows, learned skills, tool-use best practices, agent type targeting, frontmatter descriptions, reference materials, and operational output contracts. Use when creating or adapting skills for AWS De
Review Amazon DynamoDB data modeling and performance across access patterns, partition keys, sort keys, secondary indexes, GSI/LSI design, hot partitions, query versus scan behavior, capacity mode, adaptive capacity, global tables, TTL, DAX, item size, transactions, and cost. Use
Review Amazon EC2 compute operations across instances, Auto Scaling groups, Launch Templates, AMIs, Systems Manager, Patch Manager, Session Manager, EBS volumes, snapshots, health checks, instance refresh, lifecycle hooks, patch compliance, and fleet reliability. Use for EC2 day-
Review Amazon ECS and Fargate platform operations across services, task definitions, task roles, execution roles, capacity providers, load balancers, deployment circuit breakers, blue/green, autoscaling, health checks, logs, secrets, networking, and rollback. Use only for ECS/Far
Correct AWS ECS and Fargate service definitions, task definition config, deployment parameters, health checks, environment settings, and rollout wiring in-repo. Use for non-destructive repo fixes only; do not force deployments or mutate live services from this role.
Review Amazon EKS Kubernetes platform operations across cluster access, IRSA, IAM roles for service accounts, pod identity, node groups, Karpenter, autoscaling, CNI/network policy, upgrades, reliability, observability, and cost. Use only for EKS/Kubernetes; prefer ECS/Fargate ope
Review AWS event-driven system design across EventBridge, event buses, Pipes, SQS, SNS, Step Functions, event schemas, filtering, cross-account routing, retries, DLQs, replay, idempotency, monitoring, and event-loop risk. Prefer serverless production readiness for Lambda runtime/
Build Amazon Bedrock and serverless generative AI applications using Lambda, API Gateway, Step Functions, EventBridge, S3, DynamoDB, SQS, Guardrails, and IAM. Prefer this for serverless GenAI app design and implementation; prefer aws-agentcore for AgentCore runtime, aws-bedrock-a
Review AWS infrastructure-as-code changes across CDK, CloudFormation, SAM, Terraform, Serverless Framework, generated templates, plans, stack updates, change sets, and drift. Use when the user asks whether an AWS IaC deployment is safe, what a change set will do, why a resource r
Edit AWS IaC files including CloudFormation, SAM, CDK config, and Terraform to patch defects, prepare change set review, or unblock rollout work. Prefer this for bounded repo changes only; do not use for apply, deploy, or destructive infrastructure execution.
Review AWS IAM identity policies, trust policies, resource policies, permission boundaries, SCPs, session policies, role design, pass-role, federation, and Access Analyzer findings for least-privilege risk. Prefer KMS/secrets steward for key/secret lifecycle design and S3 perimet
Review AWS KMS and Secrets Manager lifecycle posture across key policies, grants, rotation, multi-Region keys, imported key material, aliases, secret rotation, replication, caching, endpoint conditions, recovery, and break-glass access. Prefer this for cryptography/secret lifecyc
Review and design AWS landing zones, AWS Control Tower environments, Organizations structures, OUs, account vending patterns, guardrails, central logging, security/audit accounts, and multi-account governance. Use when the user asks how to structure AWS accounts or govern a cloud
Operate guarded live AWS deployment changes with explicit account, region, profile, approval, dry-run, rollback, and verification gates. Use only when the target environment is confirmed and a live deployment action is intentionally requested.
Guard live Amazon ECS and Fargate rollout actions with ecs service, task definition, deployment circuit breaker, alarms, rollback, health check, and approval gates. Use only for intentional live ECS rollout actions against confirmed targets.
Guard live CloudFormation, SAM, CDK, and Terraform-backed AWS infrastructure changes with change set, drift, stack policy, rollback trigger, approval, and execute gates. Use only for intentional live IaC execution with confirmed targets.
Handle live CodePipeline approval and gated resume decisions with pipeline, stage, approver, SNS, approval, blast radius, and rollback checks. Use only when a real pipeline execution is paused or about to be approved.
Guard live Lambda and serverless release actions with lambda alias, codedeploy, canary, linear, alarms, rollback, and approval gates. Use only for intentional live serverless rollout actions against confirmed targets.
Route AWS tasks to the narrowest specialist or team of specialists from the 42-agent catalog. Use when you do not already know the specialist. Not for direct AWS answers; Maestro classifies, dispatches, and synthesizes only. Dispatches single agent for focused tasks, parallel tea
Plan, review, and de-risk AWS migrations and cutovers across discovery, dependency mapping, wave planning, AWS Application Migration Service, Migration Hub, test launches, acceptance tests, downtime windows, rollback, DNS, data consistency, and post-cutover validation. Use for mi
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.
/do-issue
do-issue
Implement issues (GitHub/GitLab/Bitbucket) using progressive analyze-specify-plan-implement workflow
/fix-pr
fix-pr
Address PR/MR review feedback by reading comments, implementing fixes, and resolving threads. GitHub and GitLab support.
/fix-workflow
fix-workflow
Retrospective analysis and improvement of workflow components with self-evolving patterns
/fixit
fixit
Fix broken functionality from pasted error output, stack traces, or
/git-catchup
git-catchup
Summarize recent git history since a baseline with structured analysis of what changed, why, and what to watch for.
/merge-docs
Merge docs
Consolidate ephemeral LLM-generated markdown into permanent documentation.
/pr-review
pr-review
Review pull requests with scope validation, code analysis, and line comments. Supports GitHub PRs and GitLab MRs.
/prepare-pr
prepare-pr
Prepare a PR end-to-end by updating documentation, running tests, dogfooding checks, and validating with code review.
/resolve-threads
resolve-threads
Batch-resolve unresolved PR/MR review threads via GraphQL API (GitHub/GitLab)
/sync-capabilities
Sync capabilities
Detect and fix drift between plugin.json registrations and capabilities reference documentation
/update-ci
Update ci
Update pre-commit hooks and CI/CD workflows based on recent project changes
/update-dependencies
update-dependencies
Scan and update dependencies across all ecosystems with conflict detection
/update-docs
Update docs
Update project documentation with consolidation, debloating, AI slop detection, capabilities sync, and accuracy verification.
/update-plugins
Update plugins
Audit and sync plugin.json registrations with actual disk contents. Detects missing or stale skills, commands, agents, hooks.
/update-tests
update-tests
Review and update test coverage using TDD/BDD methodology with quality validation. Generates tests for changed code.
/update-tutorial
update-tutorial
Generate or update tutorials with VHS and Playwright recordings
/update-version
Update version
Bump project versions using git-workspace-review and version-updates skills.
/validate-pr
validate-pr
Generate and self-execute a diff-derived test plan for a PR. Reads
/doc-generate
doc-generate
Generate new documentation with human-quality writing.
/doc-polish
doc-polish
Clean up AI-generated content and improve documentation quality.
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