LLM Mart Basic

Apply to any non-trivial work, not just bulk work: edits, migrations, analyses, checks. Build the tool that does it or proves it (codemod, script, generator, or a skill your subagents follow) instead of working by hand. The tool is the artifact a reviewer can rerun.

Apply when you catch yourself writing the same instruction a second time, or notice a recurring correction. Encode the rule as a lint, metadata flag, runtime check, or script instead of more text.

Apply when facing a novel UI interaction or architectural decision with no precedent in the codebase. Build 2-3 competing prototypes and compare side by side before committing.

Apply when product, UX, or feature-scope tradeoffs come up. Choose user delight over implementation convenience; ship fewer polished features over more rough ones.

Apply when debugging. Trace each symptom to its root cause and fix it there; reproduce first, ask why until you reach it, resist nil-check guards that silence crashes.

Apply before writing logic: choosing core types and data structures, sequencing scaffold-vs-feature work, asking what concurrent actors share. Get the data structures right so downstream code becomes obvious.

Apply when context is filling up: large outputs, long files, repeated reads, fan-out planning. Route bulk to subagents; keep summaries in the main thread, not raw payloads.

Apply when refactoring, evaluating diff size, or tempted to add abstractions, layers, or signal threading. Bias toward deletion and the smallest change that solves the problem.

Apply when designing commands, lifecycle steps, or processing loops that run amid crashes, restarts, and retries. Converge to the same end state regardless of partial prior runs.

Apply when introducing a new internal API while old callers still exist. Migrate callers and delete the old API in the same wave instead of preserving compatibility layers.

Apply when reviewing or shaping code that's hard to trace. Count layers between question and answer, and hidden state in the reader's head; collapse one-caller wrappers and shrink mutable scope.

Apply when writing stateful logic, or when code branches a lot or repeats a shape assumption across files. Encode the domain in a structure instead of scattered conditionals.

Apply when tempted to ask 'should I do X?' on reversible work. Proceed, present the result, let the human course-correct after the fact; reserve confirmation for irreversible actions.

Apply during planned rewrites and migrations with explicit phase boundaries. Converge on the target architecture; don't preserve smooth intermediate states with throwaway compatibility code.

Apply after completing a task, before declaring done. Verify against the real artifact (run the feature, read the actual value, inspect the diff), not a proxy, self-report, or 'it compiles.'

Apply when integrating a new requirement into an existing design. Redesign as if the requirement had been a foundational assumption from day one, instead of bolting it on.

Apply when concurrent actors might write to the same file, branch, key, or state object. Eliminate the sharing first; serialize structurally only when one shared writer is a real invariant.

Apply to multi-step work (sweeps, migrations, runs of similar edits) and to how you stack commits and PRs. Break work into small units that each end in a verifiable state, check each before the next, and order delivery so the sequence proves itself to a reviewer.

Apply when sequencing an addition, refactor, or rewrite. Remove dead code, redundant validators, and stub references first, then build on the simpler base.

Apply when you write, change, or keep a test. Identify a relevant defect and check that the test detects it. Assert the required result or observable effect, including absence when the contract requires it.

A green PR, a controller reporting success, and not one line of the new code running

Chart a big legal matter as a wayfinder decision map — grill the attorney breadth-first, create the map and decision tickets, fire research tickets in parallel. Planning only: charting resolves no decisions itself.

Define a checkable legal success condition for /legal-loop. Accepts a named profile (citations-clean, draft-passes-gate, adversarial-converge, nda-batch-clean, reg-watch, timeline-sourced) or free-text objective. Produces a persisted Goal Record — never starts work itself.

Iterate a worker-evaluator cycle against a Goal Record until the success condition is met or a stop limit is reached. The evaluator (a different agent than the worker) judges each iteration using MCP verification tools. Produces an auditable verdict trail and a final MET / NOT MET status.

Build a sourced legal chronology from case documents — every event with mandatory provenance, undisputed/alleged/contested status, explicit date conflicts, evidentiary gaps, and optional deadline markers. Outputs table, interactive HTML, and docx under bcc-output/timeline/.

Work one ticket from a legal-wayfinder decision map — claim a frontier ticket, resolve it by type (research / grilling / prototype / task), record the decision, graduate newly-sharp fog, and emit the handoff pack when the map is clear.

Primary entry point for all BetterCallClaude requests — classifies intent, resolves jurisdiction (via swiss-legal-research), runs inline briefing for complexity 4–6, activates full briefing session when complexity ≥ 7 (via legal-intake skill), and routes to specialist agents or workflow pipelines. Invoked explicitly as /bettercallclaude:legal or as the default when no other command matches. Supports --refine, --briefing, --skip-briefing/--direct, --no-framework flags.

Triage NDAs against Swiss law — classify as GREEN (standard) / YELLOW (review) / RED (issues) using playbook thresholds and Swiss legal criteria. Supports single file or batch (folder) mode.

Search and analyze Swiss BGE/ATF/DTF precedents with precedent chain tracking and evolution analysis

View or change the BetterCallClaude privacy mode (strict/balanced/cloud)

Refine vague legal queries into structured prompts through Socratic dialogue, with workflow recommendations and multi-lingual terminology guidance

Search Swiss legal precedents (BGE/ATF/DTF), analyze statutes, and verify citations with multi-lingual support

Check MCP server connectivity

Welcome and first-use onboarding — checks MCP connectivity, guides playbook creation, shows usage examples tailored to your profile. Replaces /setup.

Develop litigation strategy with risk assessment, procedural analysis, cost-benefit calculation, and settlement evaluation for Swiss courts

Summarize and consolidate multi-agent pipeline output -- deduplicate disclaimers, terminology, and citations with length control (--short, --medium, --long)

Translate Swiss legal documents between DE, FR, IT, and EN while preserving legal terminology precision

Validate Swiss legal citations in bulk -- check format, existence, and cross-language consistency

Display BetterCallClaude plugin version, installed components, and system status

Define and execute multi-agent legal workflows -- due diligence, litigation prep, contract lifecycle, real estate closing

Audit web accessibility for WCAG compliance with automated axe-core tests, keyboard and screen reader checks, and remediation guidance

Make any song you can imagine

Leading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars

Hermes Agent is an open-source, self-improving autonomous AI agent developed by Nous Research

Kilo Code is a popular, open-source AI coding agent and "agentic engineering" platform designed to help developers build, refactor, and debug software faster

General-purpose agent in one static Go binary. ReAct loop, ACP server for IDEs, OpenAI-compatible REST API with embedded web UI, Telegram gateway, cron schedule…

Autonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.

TSP自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台 | 基于 TickFlow 数据源 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源 ,非TickFlow官方项目

Curated, verified Agent Skills powered by ModelStudio.

Run Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…

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A persistent workspace for development work that self-improves and continues beyond one session.

Open-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.

📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…

Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.

Deterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…

Native Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…

Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.

Git for agent memory. Branches, diffs, PRs, and rollback for what your agents know.

Multi-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…

Production-grade MCP server for MikroTik RouterOS with secure AI-native network automation.