Results for “fr”

Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.

Enables persistent ultra-compressed technical communication; use for explicit brevity or token-reduction requests, except where fragments risk safety or clarity.

Control Adobe desktop apps - Photoshop, Illustrator, Premiere, After Effects, InDesign, Audition - from the shell via Flue, without an MCP server.

Build evaluation frameworks for agent systems. Use when testing agent performance systematically, validating context engineering choices, or measuring improvements over time.

Generate AGENT.md files with proper YAML frontmatter, role definitions, expertise areas, and prompt templates following Babysitter SDK conventions.

Patterns and architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems.

Create or update the project constitution from interactive or provided principle inputs, ensuring all dependent templates stay in sync.

Read, create, and convert Microsoft Word (.docx) documents — extract text and tables, build reports from markdown/JSON, and export to PDF.

Picks random winners from lists, spreadsheets, or Google Sheets for giveaways, raffles, and contests. Ensures fair, unbiased selection with transparency.

Use the model-recommender skill, Workflow C (Roster Refresh), to research and update the model roster from live benchmarks.

Move issues and external PRs through a state machine of triage roles — categorise, verify, grill if needed, and write agent-ready briefs.

Use when inferring maximum-likelihood phylogenies from aligned sequences, performing automated model selection, or assessing branch support with bootstrap or aLRT methods

Build evaluation frameworks for agent systems. Use when testing agent performance systematically, validating context engineering choices, or measuring improvements over time.

Invoke a registered skill from the current skill listing. BLOCKING REQUIREMENT: when a skill from the listing matches the user's request, you MUST call this tool (not free-form text). Do not re-invoke a skill to repeat work already done: if a `<skill-loaded>` block for it with the same `args` is already present in the conversation, follow those instructions directly instead of calling the tool again. Do call the tool again when you need the skill with different arguments — the loaded block was expanded with the earlier `args` and will not reflect new inputs.

Use acpx as a headless ACP CLI for agent-to-agent communication, always inside an isolated SubAgent. Use when running coding agents through acpx, managing persistent ACP sessions, queueing prompts, consuming structured agent output from scripts, comparing the same prompt across multiple agents, or composing multi-agent workflows with defineFlow/decision/decisionEdge. Never invoke the claude adapter (nested-instance blacklist).

You are an expert in tRPC, the framework for building type-safe APIs without schemas or code generation. You help developers create full-stack TypeScript applications where the server defines procedures and the client calls them with full type inference — no REST routes, no GraphQL schemas, no OpenAPI specs, just TypeScript functions that are type-safe from database to UI.

Search, install, update, and list agent skills from the ClawHub public registry using natural-language queries.

Set up and run HeartMuLa, the open-source music generation model family (Suno-like). Generates full songs from lyrics + tags with multilingual support.

Anti-over-engineering guardrail that activates when an AI coding agent expands scope, adds abstractions, or changes files the user did not request.

Compiled CLI covering all 52 endpoints of the Anytype local API — objects, properties, tags, search, chat, files — one binary, no MCP server needed.

Use when working from the local Biomni repository to run agent-style biomedical tasks or inspect Biomni's biomedical tool modules and examples.

Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub

Set up and run HeartMuLa, the open-source music generation model family (Suno-like). Generates full songs from lyrics + tags with multilingual support.

Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub

Agent Media OS — resolve any media need (BGM, SFX, image, icon) into a frozen local file + ledger record. One verb (`resolve`) handles the full cascade — project cache, global cache, HeyGen catalog search, freeze, register. Keeps search noise on disk, hands the agent a path. Use when a composition needs background music, sound effects, images, or icons.

Remove refusal behaviors from open-weight LLMs using OBLITERATUS — mechanistic interpretability techniques (diff-in-means, SVD, whitened SVD, LEACE, SAE decomposition, etc.) to excise guardrails while preserving reasoning. 9 CLI methods, 28 analysis modules, 116 model presets across 5 compute tiers, tournament evaluation, and telemetry-driven recommendations. Use when a user wants to uncensor, abliterate, or remove refusal from an LLM.

Detects generalizable learnings from problem-solving interactions and proposes skill updates to improve future performance.

Model any API with Swamp, test it, and enrich *Claw with new capabilities — full lifecycle from idea to working.

Debug LangChain and LangGraph agents by fetching execution traces from LangSmith. Analyze agent behavior, investigate errors, and review tool calls and performance metrics.

Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub

Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring.

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

Read, create, and convert Microsoft PowerPoint (.pptx) presentations — extract slide text to JSON/markdown, build decks from JSON/markdown outlines, and export to PDF.

Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring.

Generates speech from text using ElevenLabs TTS with local playback, supporting voice selection, pronunciation rules, and audio tags.

Configure, extend, or contribute to Hermes Agent, an open-source AI agent framework by Nous Research.