LLM Mart Basic
@llm-mart · Joined Jun 2026
Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a CONTEXT.md, or recording or editing an ADR.
A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.
Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
Build and configure Cecil static sites, with focused guidance for content, templates, and site generation.
Deliver a change through an approved design contract, sequential implementation, independent review and exact-HEAD release. Use for any Bounded or Architectural change — including a small, one-line behavioral fix, which is the canonical Bounded case — so it gets design approval a
**ANALYSIS SKILL** — Analyze any repository and generate AI-ready configuration — a canonical AGENTS.md, thin per-tool pointer files, skills, CI workflows, issue templates. WHEN: "make this repo ai-ready", "set up AI config", "add copilot instructions", "prepare this repo for AI
Global team and org memory powered by Activeloop. ALWAYS check BOTH built-in memory AND Hivemind memory when recalling information.
Create, track and update team goals via the Deeplake virtual filesystem at memory/goal/. Use whenever the user mentions a goal, objective, target, milestone, or asks to track progress on something measurable. ALSO use when the user says "task", "todo", "work item", "remind me to"
Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what's the architecture / which subsystems
Global team and org memory powered by Activeloop. ALWAYS check BOTH built-in memory AND Hivemind memory when recalling information.
Global team and org memory powered by Activeloop. ALWAYS check BOTH built-in memory AND Hivemind memory when recalling information.
Create, track and update team goals via the Deeplake virtual filesystem at memory/goal/. Use whenever the user mentions a goal, objective, target, milestone, or asks to track progress on something measurable. ALSO use when the user says "task", "todo", "work item", "remind me to"
Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what is the architecture / which subsystem
Create, track and update team goals in Hivemind via the `hivemind` CLI. Use whenever the user mentions a goal, objective, target, milestone, or asks to track progress on something measurable. ALSO use when the user says "task", "todo", "work item", "remind me to", "fix X", or any
Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what is the architecture / which subsystem
Validates and bootstraps Amazon Bedrock AgentCore observability so customers can trace
Comprehensive operational review procedures for Amazon Bedrock
Use this skill when diagnosing IAM and access failures for Bedrock and SageMaker. It traces the authorization chain — caller identity, iam:PassRole, trust policy, role permissions, resource policies, SCPs — to name the denying hop and propose a scoped policy. Read-only. Use when
Amazon OpenSearch Service domain health assessment. Performs read-only, API-driven checks against a customer's OpenSearch domain(s) covering cluster health, node/shard configuration, performance metrics, security posture, and cost optimization signals. Activate this skill for req
/optimize
Optimize
Analyze code performance and propose three specific optimization improvements
/pac-configure
Pac configure
Configure and initialize a project following the Product as Code specification for structured, version-controlled product management
/pac-create-epic
Pac create epic
Create a new epic following the Product as Code specification with guided workflow
/pac-create-ticket
Pac create ticket
Create a new ticket within an epic following the Product as Code specification
/pac-update-status
Pac update status
Update ticket status and track progress in Product as Code workflow
/pac-validate
Pac validate
Validate Product as Code project structure and files for specification compliance
/performance-audit
Performance audit
Audit application performance metrics
/pr-review
Pr review
Conduct comprehensive PR review from multiple perspectives (PM, Developer, QA, Security)
/prepare-release
Prepare release
Prepare and validate release packages
/prime
Prime
Load project context by reading key documentation files and exploring project structure
/project-health-check
Project health check
Analyze overall project health and metrics
/project-timeline-simulator
Project timeline simulator
Simulate project outcomes with variable modeling, risk assessment, and resource optimization scenarios.
/project-to-linear
Project to linear
Sync project structure to Linear workspace
/refactor-code
Refactor code
Intelligently refactor and improve code quality
/release
Release
Prepare a new release by updating changelog, version, and documentation
/remove
Remove
Safely remove a task from the orchestration system, updating all references and dependencies.
/report
Report
Generate comprehensive reports on task execution, progress, and metrics.
/repro-issue
Repro issue
Reproduce a specific issue by creating a failing test case
/resume
Resume
Resume work on existing task orchestrations after session loss or context switch.
/retrospective-analyzer
Retrospective analyzer
Analyze team retrospectives for insights
Make any song you can imagine
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