LLM Mart Basic

Phase-1 Layer-0 of the comic-author suite — turn ANY raw idea / a locked video skeleton / an audience note into ONE schema-valid intent_spec node that fixes the logline (an editorial climax), the tagline, and the named DUAL-IDENTITY design constraint the whole comic optimizes aga

Phase-1 (S9, the FINAL comic-author step) — assemble the LOCKED storyboard + locked per-panel blueprints into ONE schema-valid `comic.json` (the comic-ir/1.0 contract boundary handed to comic-director / run_comic.py). Project the page_order + each panel's condition{} + render fie

Phase-1 Layer-2 of a comic — turn a LOCKED skeleton (intent_spec + the pre-locked beat/shot list) into an approved outline_spec: a 6-column beat table that binds every ARIS capability to a STORY COST, plus the continuity-motif contract the storyboard layer will be held to. NOT fr

Phase-1 step of comic-author — the DETERMINISTIC compiler (搬运工原則) that turns ONE gate-approved panel_spec + its status:locked blueprint into the EXACT fixed-section bake string for the spiral engine via the shipped scripts/build_prompt.py (+ the canonical scripts/_validate.py vet

Phase-1 comic-author step — turn a LOCKED, user-approved outline into the page-first storyboard that IS the authoring source of truth: a fixed page order BEFORE any prose, the MOTIF STATE TABLE (the master per-panel continuity ledger), a fixed 9-field per-panel spec, and one dedu

Phase-1 (S2) of the comic-author suite — compile the project's ART_BIBLE.md into an EXECUTABLE convergence target, not aesthetic prose. The bible is the ONE visual dialect read verbatim into every bake prompt AND into every visual reviewer's rubric (`style_consistency`/`identity_

Generate a publication-grade method / architecture / pipeline / workflow figure (a paper or README 'Figure 1') as an AUDITABLE object, not a one-shot prompt. A deterministic JSON blueprint LOCKS the content; an image model (gpt-image-2, baked by the agent via mcp__codex__codex —

End-to-end Pipeline A in ONE slash-command — turn a fuzzy story idea into a cross-model-audited, image-based movie + a clickable viewer. Chains comic-author (Phase 1 — intent→style→outline draft→provisional storyboard→assets→final locks→blueprints→prompts→comic.json) → the zero-c

Analyze architecture for consistency between ADRs and AD, completeness, and quality issues. Use when validating generated or refined architecture artifacts, before feature development, during architecture review, or periodically to detect drift.

Generate a full Architecture Description (AD.md) from accepted ADRs using multi-agent DAG orchestration. Use when accepted ADRs exist and you need to produce or update unified architecture documentation.

Review, accept, reject, or defer Change Decision Records (ChDRs) discovered by change-init. Interactive one-ChDR-at-a-time workflow that validates inferred decisions against their git/issue evidence before promotion to project memory.

Mine git history for Change Decision Records (ChDRs) by detecting commit messages that link to issue trackers, clustering the commits into change stories, and inferring the decisions behind them. Use when bootstrapping project memory from an existing repo's history (brownfield),

Promote accepted Change Decision Records (ChDRs) from drafts to project memory at .adlc/memory/chdr/, write OKF-style frontmatter, and regenerate the boot-facing .adlc/memory/chdr.md index that team-boot injects at session start. Use after /change-clarify has accepted ChDRs.

Analyze evaluation results and close the loop. Specification failures create local CDRs to fix agent rules; generalization failures go to evaluator backlog.

Refine, cluster, and accept draft criteria into the published goldset. Isolates 20% holdout split and publishes goldset.md + goldset.json.

Generate executable graders and configs from goldset. Generates Python graders / metrics and auto-runs unit tests to verify grader correctness.

Initialize evals/{system}/ directory structure for evaluation system following EDD principles (Standalone). Choose PromptFoo or DeepEval based on tech stack, generate security baseline.

Extract eval criteria from product specs and production failure traces (bottom-up error analysis). Writes proposed criteria to .adlc/drafts/evals/.

Run evaluations and validate evaluator quality (SLA compliance, TPR/TNR, statistical accuracy). Executes PromptFoo or pytest DeepEval.

Read-only analysis of PDR↔PRD consistency, PDR quality, cross-PDR conflicts, and staleness. Outputs a structured markdown report with severity-assigned findings. Use after /product-implement or periodically to detect drift.

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

Run a UI code review on the current snippet — Before / After / Why table per review-format, scoped to review-checklist.

Scan UI or marketing copy for AI-default tells and content-authenticity misses — deletion list, not a redesign brief.

Decide which moments earn a sound, design one material family, generate the files (ElevenLabs if keyed, synth or CC0 if not), and wire them in — returns a sound map table.

Animate an SVG — icon, logo reveal, stroke draw, morph, mascot loop — or turn a frame sequence / flat clip into one editable animated SVG, with the engine chosen for where the file lives.

Author or clean up an SVG asset — icon, illustration, mascot pose, logo mark — so it scales from viewBox, recolors from tokens, animates without a rewrite, is optimized, and has an accessible name.

Close a Context OS session through its review-gated workflow

Set up Context OS through its review-gated lifecycle workflow

Start a read-only Context OS continuity review

Save a review-gated Context OS checkpoint

Route broad repository discovery to a cheaper worker model using each client's native subagents, keeping the main agent for decisions and targeted verification. Use when asked to "reduce token usage", "delegate bulk reading", "set up a cheap reader agent", or "why is my context filling up".

Generate LEARNINGS.md from skill execution logs over a configurable time window.

Analyze skill file complexity metrics and generate modularization recommendations for splitting or progressive loading.

Generate context optimization report for skill directories

Create slash commands with brainstorming and best practices

Create hooks with brainstorming and security-first design

Scaffold new Claude Code skills with brainstorming, TDD methodology, and proper frontmatter and module structure.

Manually evaluate a recent skill execution to record qualitative feedback.

Evaluate all hooks in a plugin for quality and compliance

Identify and implement skill improvements from execution logs and user evaluations.

Analyze and enhance Makefiles for complete functionality coverage with auto-generation capability

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.