ThinkfleetAI

Use when working with Resend email platform - routes to specific sub-skills for sending, receiving, audiences, or broadcasts.

Control Bambu Lab 3D printers locally via MQTT (no cloud). Supports A1, A1 Mini, P1P, P1S, X1C.

CLI for the onchain agent messaging layer on the Base blockchain, built on Net Protocol. Explore other agents, post to feeds, send direct messages, and store information permanently onchain.

Check Claude Code OAuth usage limits (session & weekly quotas). Use when user asks about Claude Code usage, remaining limits, rate limits, or how much Claude usage they have left. Includes automated session refresh reminders and reset detection monitoring.

Run Codex CLI, Claude Code, OpenCode, or Pi Coding Agent via background process for programmatic control.

Text-to-speech conversion using node-edge-tts npm package for generating audio from text. Supports multiple voices, languages, speed adjustment, pitch control, and subtitle generation. Use when: (1) User requests audio/voice output with the "tts" trigger or…

Set your primary ENS name on Base and other L2s. Use when user wants to set their ENS name, configure reverse resolution, set primary name, or make their address resolve to an ENS name. Supports Base, Arbitrum, Optimism, and Ethereum mainnet.

Register AI agents on Ethereum mainnet using ERC-8004 (Trustless Agents). Use when the user wants to register their agent identity on-chain, create an agent profile, claim an agent NFT, set up agent reputation, or make their agent discoverable. Handles…

Surface emergent behavior patterns MemMesh has mined from a subject's history — recurring habits nobody predefined, each with prevalence, stability, and the evidence behind it. Use when the user asks "what patterns do you see", "what are this user's habits",…

Load relevant MemMesh context before starting work — searches memory and, for a specific subject, assembles a token-budgeted bundle (profile + behavior patterns + forward predictions + top memories) in one call. Use when beginning a task, switching context,…

Query MemMesh's bi-temporal knowledge graph — multi-hop reasoning across entities, point-in-time "what did we believe on date X", and anticipatory retrieval via spreading activation. Use for questions no single stored fact answers, or to see how knowledge…

Forecast what a subject will do next from their mined behavior patterns — with a calibrated, horizon-decayed confidence and provenance. Use when the user asks "what is this user/account likely to do next", "will X churn/convert/ reorder", or wants a forward…

Explain a MemMesh prediction or recalled fact — surface its provenance (evidence memories), its calibrated confidence, and whether the model abstained and why. Use when the user asks "why do you think that", "what's this based on", "how sure are you", or…

Run MemMesh's competitive benchmark harness (LOCOMO / BEAM) to compare retrieval quality, tokens, latency, and cost against Mem0, Zep, full-context, and naive-RAG baselines. Use when the user wants proof MemMesh is better, is evaluating a migration, or asks…

Consolidate MemMesh memories — find duplicates and contradictions, merge or supersede them, and retire stale entries — to keep search results clean. Use when memory count is high, search feels noisy/repetitive, or for periodic hygiene. Respects pinned…

Export MemMesh memories for a project/user to a portable Markdown (or JSONL) file for backup, migration, or sharing. Use when backing up, moving to another project, sharing memory state with teammates, or archiving before a cleanup.

Persist the durable signal from this conversation into the user's MemMesh memory as you work. Use throughout and at the end of any working session — especially when the user states a lasting fact, makes a decision, reveals a preference, or walks through a…