LLM Mart Basic
@llm-mart · Joined Jun 2026
Deploy an AI legal operations agent for contract review, regulatory monitoring, policy enforcement, audit preparation, and document management. Complete Hermes configuration blueprint.
Deploy an AI marketing agent for SEO monitoring, campaign analytics, content performance, competitive intelligence, and social scheduling. Complete Hermes blueprint with cron and connectors.
Deploy an AI research agent for competitor monitoring, market intelligence, academic literature reviews, patent tracking, and news aggregation. Complete Hermes configuration blueprint.
Deploy an autonomous Hermes sales agent for lead qualification, pipeline management, outreach sequences, and daily CRM reporting. Complete configuration blueprint with cron schedules.
Deploy an AI customer support agent for ticket triage, knowledge base search, response drafting, SLA monitoring, and trending issue detection. Complete Hermes configuration blueprint.
Recommend AND run open-source AI tools, agents, Claude Code / Codex skills, and MCP servers for any stage of a literature review — searching, reading, extracting, synthesizing, screening, citation-checking, and paper writing. Use when the user asks "what tool should I use to..."
Orchestrate many forge runs at once: analyze which tasks collide on the same files, schedule the colliding ones sequentially, and run the rest in parallel worktrees at the right model tier and review depth. Use when the user runs /blacksmith-orchestrate or asks to ship several is
Brainstorm UI/UX changes into an approved design through interactive browser proposals rendered in the project's real design language. Option clicks assemble a response prompt copied to the user's clipboard. Use when the user runs /blueprint or wants to brainstorm, redesign, or v
Forge an issue, ticket, or PR into a shipped fix: propose a plan, get it approved, then implement, review, and refactor. Use when the user runs /forge or asks to investigate, fix, resolve, triage, or solve one. See Parameters for modifier flags.
Manage Todoist tasks, projects, labels, filters, sections, comments, reminders, and workspaces via the `td` CLI. Use when the user wants to view, create, update, complete, or organize Todoist items, or mentions tasks, inbox, today, upcoming, projects, labels, or filters.
Guide for adding new CLI commands or subcommands to todoist-cli. Use when implementing new SDK endpoints, adding subcommands to existing command groups, or extending CLI functionality.
Guide for adding new CLI commands or subcommands to todoist-cli. Use when implementing new SDK endpoints, adding subcommands to existing command groups, or extending CLI functionality.
Use when composing an ask_user_question round inside a workflow, or when a workflow skill names it at a question step. Shared norms for the tool — not a workflow, nothing to execute.
Use this BEFORE any creative or feature work: building a new feature, adding functionality, changing behavior, or making a nontrivial design decision. Turns the user's request into a validated design — recorded as a spec-graph task-spec — before any implementation. Do not skip th
Use FIRST when any new piece of work arrives — a request, feature, change, fix, question, or idea — before starting on it or choosing an approach. Not for continuing work already routed to a workflow skill.
Use when the repo holds real source code but no specs: the existing-codebase branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for empty workspaces (starting-a-new-project) or feature work in a specced proj
Use whenever asked to set up, onboard, initialize, or spec a project — the front door when the workspace has no spec graph yet (brand-new or an existing codebase); also seeded by the app's Set-up-project card (/skill:setting-up-a-project). Not for feature work in an already-specc
Use when finished work needs to ship as a pull request, or when the ask is about a PR — creating one, bringing it up to date, adding screenshots, watching its checks, or addressing its review comments. Not for reviewing a PR you are not shipping.
Use when the workspace is empty — no code yet — and the user brings a raw idea: the brand-new branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for features in an existing project — use brainstorming instea
Use when a workflow step drafts or revises a spec artifact — a goal-and-requirements, an architecture, or a module SPEC — or when a workflow skill names it at such a step. The shared quality bar for specs — not a workflow, nothing to execute.
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.
/plan-es
Plan es
Iniciar planificación de archivos estilo Manus. Crear task_plan.md, findings.md, progress.md para tareas complejas.
/plan-goal
Plan goal
Bridge Claude Code's /goal to the active plan. Derives a goal condition from task_plan.md and invokes /goal so Claude keeps working until the plan is complete. Available since v2.38.0.
/plan-loop
Plan loop
Run a planning-aware cadence with Claude Code's /loop. Default tick checks plan status, runs check-complete, nudges progress.md update if stalled. Available since v2.38.0.
/plan-zh
Plan zh
启动 Manus 风格的文件规划。为复杂任务创建 task_plan.md、findings.md、progress.md。
/plan-zht
Plan zht
啟動 Manus 風格的檔案規劃。為複雜任務建立 task_plan.md、findings.md、progress.md。
/plan
Plan
Start Manus-style file-based planning. Creates task_plan.md, findings.md, progress.md for complex tasks.
/pwf
Pwf
Short alias for /plan. Starts Manus-style file-based planning: task_plan.md, findings.md, progress.md. Available since v3.0.0.
/start
Start
Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls. Now with automatic session recovery after /clear
/status
Status
Show current planning status at a glance - phases, progress, and any logged errors.
/adversarial
Adversarial
Run three-agent adversarial analysis -- advocate builds the case, adversary challenges it, judicial analyst synthesizes
/briefing
Briefing
Structured pre-execution briefing session -- collects case context through specialist panel, builds execution plan, supports resume and depth control
/cantonal
Cantonal
Analyze cantonal law for all 26 Swiss cantons -- cantonal court decisions, cantonal legislation, procedural specifics, and interaction with federal law
/cite
Cite
Validate, format, and look up Swiss legal citations including BGE/ATF/DTF decisions and statutory references
/create-workflow
Create workflow
Create a reusable custom workflow by combining BetterCallClaude agents. Interview-based: pick agents, order them, define the output. Saved for future use with /bettercallclaude:workflow.
/doc-analyze
Doc analyze
Analyze Swiss legal documents -- identify legal issues, extract key clauses, verify citations, and assess compliance
/doctor
Doctor
Diagnose MCP server connectivity — tests each server, reports status and impact in plain language, suggests fixes for issues.
/draft
Draft
Draft Swiss legal documents including contracts (OR), court submissions (ZPO), and legal opinions (Gutachten) with multi-lingual support
/federal
Federal
Force Federal Law Mode for Swiss federal legal analysis, overriding cantonal auto-detection
/help
Help
Show complete BetterCallClaude command reference, available agents, skills, and usage examples
/legal-5step
Legal 5step
Execute the BetterCallClaude 5-step Swiss legal framework: intake → research → strategy → adversarial → draft. A complete end-to-end pipeline for any Swiss legal matter, from document analysis through final legal output.
An open-source, privacy-first, self-hosted knowledge workspace where humans and AI agents work together 开源、隐私优先、自托管的知识工作空间,让人与智能体在此协作
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