HuggingMes sync [r-louissoume-hugging-hermes-p3g5rhd2-9cf40-smzzs] 2026-05-16T17:09:52Z

.local/share/tirith/log.jsonl

@@ -136,3 +136,10 @@
 {"timestamp":"2026-05-16T16:56:28.772233007+00:00","session_id":"5dad5213-0ee0-42af-a695-1d0c6e9a8f07","action":"Allow","rule_ids":[],"command_redacted":"curl -s -H \"ngrok-skip-browser-warning: true\" \"$WINDOWS_MCP_URL/screenshot\" -o s[...redacted 13 bytes]","bypass_requested":false,"bypass_honored":false,"interactive":false,"policy_path":null,"event_id":"68f0c24b-f719-4fd7-a563-f7f5e78f30d6","tier_reached":3,"entry_type":"verdict","raw_action":"Allow","raw_rule_ids":[]}
 {"timestamp":"2026-05-16T16:57:34.227304939+00:00","session_id":"5dad5213-0ee0-42af-a695-1d0c6e9a8f07","action":"Allow","rule_ids":[],"command_redacted":"pip install pywinauto","bypass_requested":false,"bypass_honored":false,"interactive":false,"policy_path":null,"event_id":"49b60a60-2f15-4487-a899-57705468d62b","tier_reached":3,"entry_type":"verdict","raw_action":"Allow","raw_rule_ids":[]}
 {"timestamp":"2026-05-16T16:57:39.799460546+00:00","session_id":"5dad5213-0ee0-42af-a695-1d0c6e9a8f07","action":"Allow","rule_ids":[],"command_redacted":"apt-get update && apt-get install -y python3-pip","bypass_requested":false,"bypass_honored":false,"interactive":false,"policy_path":null,"event_id":"f764659b-eec9-4b77-9ba1-19546fc51fce","tier_reached":1,"entry_type":"verdict","raw_action":"Allow","raw_rule_ids":[]}
+{"timestamp":"2026-05-16T16:58:59.942326116+00:00","session_id":"5dad5213-0ee0-42af-a695-1d0c6e9a8f07","action":"Allow","rule_ids":[],"command_redacted":"env | grep WINDOWS_MCP_URL","bypass_requested":false,"bypass_honored":false,"interactive":false,"policy_path":null,"event_id":"58b8f84f-d539-4013-adb6-fb41cb1bb1a9","tier_reached":1,"entry_type":"verdict","raw_action":"Allow","raw_rule_ids":[]}
+{"timestamp":"2026-05-16T16:59:06.395504163+00:00","session_id":"5dad5213-0ee0-42af-a695-1d0c6e9a8f07","action":"Allow","rule_ids":[],"command_redacted":"curl -H \"ngrok-skip-browser-warning: true\" $WINDOWS_MCP_URL/screenshot -o screen[...redacted 8 bytes]","bypass_requested":false,"bypass_honored":false,"interactive":false,"policy_path":null,"event_id":"dc4734a3-6a5c-43a4-bb9c-7a213bdfd882","tier_reached":3,"entry_type":"verdict","raw_action":"Allow","raw_rule_ids":[]}
+{"timestamp":"2026-05-16T16:59:17.192818803+00:00","session_id":"5dad5213-0ee0-42af-a695-1d0c6e9a8f07","action":"Allow","rule_ids":[],"command_redacted":"nslookup analysis-environmental-motels-warming.trycloudflare.com","bypass_requested":false,"bypass_honored":false,"interactive":false,"policy_path":null,"event_id":"9ee2f124-857a-404c-9d3c-31191f013514","tier_reached":1,"entry_type":"verdict","raw_action":"Allow","raw_rule_ids":[]}
+{"timestamp":"2026-05-16T17:05:09.214531465+00:00","session_id":"5dad5213-0ee0-42af-a695-1d0c6e9a8f07","action":"Allow","rule_ids":[],"command_redacted":"powershell -Command \"Start-Process notepad; Start-Sleep -Seconds 1; $wshell = Ne[...redacted 120 bytes]","bypass_requested":false,"bypass_honored":false,"interactive":false,"policy_path":null,"event_id":"59777319-d0ee-4daa-b752-df7dadc34987","tier_reached":1,"entry_type":"verdict","raw_action":"Allow","raw_rule_ids":[]}
+{"timestamp":"2026-05-16T17:05:22.780996151+00:00","session_id":"5dad5213-0ee0-42af-a695-1d0c6e9a8f07","action":"Allow","rule_ids":[],"command_redacted":"env | grep WINDOWS_MCP_URL","bypass_requested":false,"bypass_honored":false,"interactive":false,"policy_path":null,"event_id":"1d92b238-8157-42ff-a4a6-42d2b0373105","tier_reached":1,"entry_type":"verdict","raw_action":"Allow","raw_rule_ids":[]}
+{"timestamp":"2026-05-16T17:05:48.584142373+00:00","session_id":"5dad5213-0ee0-42af-a695-1d0c6e9a8f07","action":"Allow","rule_ids":[],"command_redacted":"cat /opt/data/skills/mcp/windows-remote-control/scripts/decode_screenshot.py","bypass_requested":false,"bypass_honored":false,"interactive":false,"policy_path":null,"event_id":"0bc903c0-2e40-4b9b-84c0-ca641850161a","tier_reached":1,"entry_type":"verdict","raw_action":"Allow","raw_rule_ids":[]}
+{"timestamp":"2026-05-16T17:06:20.439443043+00:00","session_id":"5dad5213-0ee0-42af-a695-1d0c6e9a8f07","action":"Allow","rule_ids":[],"command_redacted":"curl -H \"ngrok-skip-browser-warning: true\" https://analysis-environmental-motels[...redacted 65 bytes]","bypass_requested":false,"bypass_honored":false,"interactive":false,"policy_path":null,"event_id":"eb094588-eb86-46c2-9922-73310b9d785a","tier_reached":3,"entry_type":"verdict","raw_action":"Allow","raw_rule_ids":[]}

channel_directory.json

@@ -1,5 +1,5 @@
 {
-  "updated_at": "2026-05-16T16:58:47.745785",
+  "updated_at": "2026-05-16T17:08:47.800840",
   "platforms": {
     "telegram": [
       {

sessions/session_api-1753f9a0255e73fb.json

@@ -4,7 +4,7 @@
   "base_url": "https://integrate.api.nvidia.com/v1",
   "platform": "api_server",
   "session_start": "2026-05-16T16:57:28.706649",
-  "last_updated": "2026-05-16T16:58:50.879442",
+  "last_updated": "2026-05-16T16:59:46.008235",
   "system_prompt": "# Hermes Agent Persona\n\n<!--\nThis file defines the agent's personality and tone.\nThe agent will embody whatever you write here.\nEdit this to customize how Hermes communicates with you.\n\nExamples:\n  - \"You are a warm, playful assistant who uses kaomoji occasionally.\"\n  - \"You are a concise technical expert. No fluff, just facts.\"\n  - \"You speak like a friendly coworker who happens to know everything.\"\n\nThis file is loaded fresh each message -- no restart needed.\nDelete the contents (or this file) to use the default personality.\n-->\n\nIf the user asks about configuring, setting up, or using Hermes Agent itself, load the `hermes-agent` skill with skill_view(name='hermes-agent') before answering. Docs: https://hermes-agent.nousresearch.com/docs\n\nYou have persistent memory across sessions. Save durable facts using the memory tool: user preferences, environment details, tool quirks, and stable conventions. Memory is injected into every turn, so keep it compact and focused on facts that will still matter later.\nPrioritize what reduces future user steering — the most valuable memory is one that prevents the user from having to correct or remind you again. User preferences and recurring corrections matter more than procedural task details.\nDo NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts. Specifically: do not record PR numbers, issue numbers, commit SHAs, 'fixed bug X', 'submitted PR Y', 'Phase N done', file counts, or any artifact that will be stale in 7 days. If a fact will be stale in a week, it does not belong in memory. If you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool.\nWrite memories as declarative facts, not instructions to yourself. 'User prefers concise responses' ✓ — 'Always respond concisely' ✗. 'Project uses pytest with xdist' ✓ — 'Run tests with pytest -n 4' ✗. Imperative phrasing gets re-read as a directive in later sessions and can cause repeated work or override the user's current request. Procedures and workflows belong in skills, not memory. When the user references something from a past conversation or you suspect relevant cross-session context exists, use session_search to recall it before asking them to repeat themselves. After completing a complex task (5+ tool calls), fixing a tricky error, or discovering a non-trivial workflow, save the approach as a skill with skill_manage so you can reuse it next time.\nWhen using a skill and finding it outdated, incomplete, or wrong, patch it immediately with skill_manage(action='patch') — don't wait to be asked. Skills that aren't maintained become liabilities.\n\n## Skills (mandatory)\nBefore replying, scan the skills below. If a skill matches or is even partially relevant to your task, you MUST load it with skill_view(name) and follow its instructions. Err on the side of loading — it is always better to have context you don't need than to miss critical steps, pitfalls, or established workflows. Skills contain specialized knowledge — API endpoints, tool-specific commands, and proven workflows that outperform general-purpose approaches. Load the skill even if you think you could handle the task with basic tools like web_search or terminal. Skills also encode the user's preferred approach, conventions, and quality standards for tasks like code review, planning, and testing — load them even for tasks you already know how to do, because the skill defines how it should be done here.\nWhenever the user asks you to configure, set up, install, enable, disable, modify, or troubleshoot Hermes Agent itself — its CLI, config, models, providers, tools, skills, voice, gateway, plugins, or any feature — load the `hermes-agent` skill first. It has the actual commands (e.g. `hermes config set …`, `hermes tools`, `hermes setup`) so you don't have to guess or invent workarounds.\nIf a skill has issues, fix it with skill_manage(action='patch').\nAfter difficult/iterative tasks, offer to save as a skill. If a skill you loaded was missing steps, had wrong commands, or needed pitfalls you discovered, update it before finishing.\n\n<available_skills>\n  autonomous-ai-agents: Skills for spawning and orchestrating autonomous AI coding agents and multi-agent workflows — running independent agent processes, delegating tasks, and coordinating parallel workstreams.\n    - claude-code: Delegate coding to Claude Code CLI (features, PRs).\n    - codex: Delegate coding to OpenAI Codex CLI (features, PRs).\n    - hermes-agent: Configure, extend, or contribute to Hermes Agent.\n    - opencode: Delegate coding to OpenCode CLI (features, PR review).\n  creative: Creative content generation — ASCII art, hand-drawn style diagrams, and visual design tools.\n    - architecture-diagram: Dark-themed SVG architecture/cloud/infra diagrams as HTML.\n    - ascii-art: ASCII art: pyfiglet, cowsay, boxes, image-to-ascii.\n    - ascii-video: ASCII video: convert video/audio to colored ASCII MP4/GIF.\n    - baoyu-comic: Knowledge comics (知识漫画): educational, biography, tutorial.\n    - baoyu-infographic: Infographics: 21 layouts x 21 styles (信息图, 可视化).\n    - claude-design: Design one-off HTML artifacts (landing, deck, prototype).\n    - comfyui: Generate images, video, and audio with ComfyUI — install,...\n    - design-md: Author/validate/export Google's DESIGN.md token spec files.\n    - excalidraw: Hand-drawn Excalidraw JSON diagrams (arch, flow, seq).\n    - humanizer: Humanize text: strip AI-isms and add real voice.\n    - ideation: Generate project ideas via creative constraints.\n    - manim-video: Manim CE animations: 3Blue1Brown math/algo videos.\n    - p5js: p5.js sketches: gen art, shaders, interactive, 3D.\n    - pixel-art: Pixel art w/ era palettes (NES, Game Boy, PICO-8).\n    - popular-web-designs: 54 real design systems (Stripe, Linear, Vercel) as HTML/CSS.\n    - pretext: Use when building creative browser demos with @chenglou/p...\n    - sketch: Throwaway HTML mockups: 2-3 design variants to compare.\n    - songwriting-and-ai-music: Songwriting craft and Suno AI music prompts.\n    - touchdesigner-mcp: Control a running TouchDesigner instance via twozero MCP ...\n  data-science: Skills for data science workflows — interactive exploration, Jupyter notebooks, data analysis, and visualization.\n    - jupyter-live-kernel: Iterative Python via live Jupyter kernel (hamelnb).\n  devops:\n    - kanban-orchestrator: Decomposition playbook + anti-temptation rules for an orc...\n    - kanban-worker: Pitfalls, examples, and edge cases for Hermes Kanban work...\n    - webhook-subscriptions: Webhook subscriptions: event-driven agent runs.\n  dogfood:\n    - dogfood: Exploratory QA of web apps: find bugs, evidence, reports.\n  ecommerce:\n    - shopify-product-research: Automated product research agent for Shopify stores - fin...\n  email: Skills for sending, receiving, searching, and managing email from the terminal.\n    - himalaya: Himalaya CLI: IMAP/SMTP email from terminal.\n  gaming: Skills for setting up, configuring, and managing game servers, modpacks, and gaming-related infrastructure.\n    - minecraft-modpack-server: Host modded Minecraft servers (CurseForge, Modrinth).\n    - pokemon-player: Play Pokemon via headless emulator + RAM reads.\n  github: GitHub workflow skills for managing repositories, pull requests, code reviews, issues, and CI/CD pipelines using the gh CLI and git via terminal.\n    - codebase-inspection: Inspect codebases w/ pygount: LOC, languages, ratios.\n    - github-auth: GitHub auth setup: HTTPS tokens, SSH keys, gh CLI login.\n    - github-code-review: Review PRs: diffs, inline comments via gh or REST.\n    - github-issues: Create, triage, label, assign GitHub issues via gh or REST.\n    - github-pr-workflow: GitHub PR lifecycle: branch, commit, open, CI, merge.\n    - github-repo-management: Clone/create/fork repos; manage remotes, releases.\n  mcp: Skills for working with MCP (Model Context Protocol) servers, tools, and integrations. Documents the built-in native MCP client — configure servers in config.yaml for automatic tool discovery.\n    - native-mcp: MCP client: connect servers, register tools (stdio/HTTP).\n    - windows-remote-control: Mandatory protocol for interacting with Windows PC via ng...\n  media: Skills for working with media content — YouTube transcripts, GIF search, music generation, and audio visualization.\n    - gif-search: Search/download GIFs from Tenor via curl + jq.\n    - heartmula: HeartMuLa: Suno-like song generation from lyrics + tags.\n    - songsee: Audio spectrograms/features (mel, chroma, MFCC) via CLI.\n    - spotify: Spotify: play, search, queue, manage playlists and devices.\n    - youtube-content: YouTube transcripts to summaries, threads, blogs.\n  mlops: Knowledge and Tools for Machine Learning Operations - tools and frameworks for training, fine-tuning, deploying, and optimizing ML/AI models\n    - gemini-key-rotator: Automatically rotates Gemini API keys on quota errors by ...\n    - huggingface-hub: HuggingFace hf CLI: search/download/upload models, datasets.\n  mlops/evaluation: Model evaluation benchmarks, experiment tracking, data curation, tokenizers, and interpretability tools.\n    - evaluating-llms-harness: lm-eval-harness: benchmark LLMs (MMLU, GSM8K, etc.).\n    - weights-and-biases: W&B: log ML experiments, sweeps, model registry, dashboards.\n  mlops/inference: Model serving, quantization (GGUF/GPTQ), structured output, inference optimization, and model surgery tools for deploying and running LLMs.\n    - llama-cpp: llama.cpp local GGUF inference + HF Hub model discovery.\n    - obliteratus: OBLITERATUS: abliterate LLM refusals (diff-in-means).\n    - outlines: Outlines: structured JSON/regex/Pydantic LLM generation.\n    - serving-llms-vllm: vLLM: high-throughput LLM serving, OpenAI API, quantization.\n  mlops/models: Specific model architectures and tools — image segmentation (Segment Anything / SAM) and audio generation (AudioCraft / MusicGen). Additional model skills (CLIP, Stable Diffusion, Whisper, LLaVA) are available as optional skills.\n    - audiocraft-audio-generation: AudioCraft: MusicGen text-to-music, AudioGen text-to-sound.\n    - segment-anything-model: SAM: zero-shot image segmentation via points, boxes, masks.\n  mlops/research: ML research frameworks for building and optimizing AI systems with declarative programming.\n    - dspy: DSPy: declarative LM programs, auto-optimize prompts, RAG.\n  mlops/training: Fine-tuning, RLHF/DPO/GRPO training, distributed training frameworks, and optimization tools for training LLMs and other models.\n    - axolotl: Axolotl: YAML LLM fine-tuning (LoRA, DPO, GRPO).\n    - fine-tuning-with-trl: TRL: SFT, DPO, PPO, GRPO, reward modeling for LLM RLHF.\n    - unsloth: Unsloth: 2-5x faster LoRA/QLoRA fine-tuning, less VRAM.\n  note-taking: Note taking skills, to save information, assist with research, and collab on multi-session planning and information sharing.\n    - obsidian: Read, search, create, and edit notes in the Obsidian vault.\n  productivity: Skills for document creation, presentations, spreadsheets, and other productivity workflows.\n    - airtable: Airtable REST API via curl. Records CRUD, filters, upserts.\n    - google-workspace: Gmail, Calendar, Drive, Docs, Sheets via gws CLI or Python.\n    - linear: Linear: manage issues, projects, teams via GraphQL + curl.\n    - maps: Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.\n    - nano-pdf: Edit PDF text/typos/titles via nano-pdf CLI (NL prompts).\n    - notion: Notion API + ntn CLI: pages, databases, markdown, Workers.\n    - ocr-and-documents: Extract text from PDFs/scans (pymupdf, marker-pdf).\n    - powerpoint: Create, read, edit .pptx decks, slides, notes, templates.\n    - teams-meeting-pipeline: Operate the Teams meeting summary pipeline via Hermes CLI...\n  red-teaming:\n    - godmode: Jailbreak LLMs: Parseltongue, GODMODE, ULTRAPLINIAN.\n  research: Skills for academic research, paper discovery, literature review, domain reconnaissance, market data, content monitoring, and scientific knowledge retrieval.\n    - arxiv: Search arXiv papers by keyword, author, category, or ID.\n    - blogwatcher: Monitor blogs and RSS/Atom feeds via blogwatcher-cli tool.\n    - llm-wiki: Karpathy's LLM Wiki: build/query interlinked markdown KB.\n    - polymarket: Query Polymarket: markets, prices, orderbooks, history.\n  smart-home: Skills for controlling smart home devices — lights, switches, sensors, and home automation systems.\n    - openhue: Control Philips Hue lights, scenes, rooms via OpenHue CLI.\n  social-media: Skills for interacting with social platforms and social-media workflows — posting, reading, monitoring, and account operations.\n    - xurl: X/Twitter via xurl CLI: post, search, DM, media, v2 API.\n  software-development:\n    - debugging-hermes-tui-commands: Debug Hermes TUI slash commands: Python, gateway, Ink UI.\n    - hermes-agent-skill-authoring: Author in-repo SKILL.md: frontmatter, validator, structure.\n    - node-inspect-debugger: Debug Node.js via --inspect + Chrome DevTools Protocol CLI.\n    - plan: Plan mode: write markdown plan to .hermes/plans/, no exec.\n    - python-debugpy: Debug Python: pdb REPL + debugpy remote (DAP).\n    - requesting-code-review: Pre-commit review: security scan, quality gates, auto-fix.\n    - spike: Throwaway experiments to validate an idea before build.\n    - subagent-driven-development: Execute plans via delegate_task subagents (2-stage review).\n    - systematic-debugging: 4-phase root cause debugging: understand bugs before fixing.\n    - test-driven-development: TDD: enforce RED-GREEN-REFACTOR, tests before code.\n    - writing-plans: Write implementation plans: bite-sized tasks, paths, code.\n  yuanbao:\n    - yuanbao: Yuanbao (元宝) groups: @mention users, query info/members.\n</available_skills>\n\nOnly proceed without loading a skill if genuinely none are relevant to the task.\n\nHost: Linux (6.12.80-106.156.amzn2023.x86_64)\nUser home directory: /opt/data\nCurrent working directory: /opt/hermes\n\nYou're responding through an API server. The rendering layer is unknown — assume plain text. No markdown formatting (no asterisks, bullets, headers, code fences). Treat this like a conversation, not a document. Keep responses brief and natural.\n\n══════════════════════════════════════════════\nMEMORY (your personal notes) [21% — 463/2,200 chars]\n══════════════════════════════════════════════\nI am deployed on Hugging Face and currently lack the `web_search` tool. It cannot be enabled from within our conversation; it requires modification of the Hugging Face Space/Endpoint configuration or contacting its maintainer.\n§\nLouis expects me to control his local Windows machine via custom ngrok endpoints for screenshotting, clicking, typing, and scrolling. He prefers iterative troubleshooting when tasks (like file creation) fail to manifest on his screen.\n\n══════════════════════════════════════════════\nUSER PROFILE (who the user is) [90% — 1,245/1,375 chars]\n══════════════════════════════════════════════\nThe user's name is Louis.\n§\nLouis wants me to be his \"right-hand man\" for his daily projects.\n§\nLouis wants me to learn from each of our conversations.\n§\nLouis prefers concise responses by default but wants necessary details included when required for task completion - he values brevity to manage API token usage but accepts detail when essential.\n§\nThe user wants to be able to specify the model version used for tasks like scheduled jobs or delegated tasks, and has expressed a desire to modify the model at the source. The user also asked multiple times about the model I am currently running on.\n§\nThe user prefers concise responses.\n§\nLouis prefers AI systems where specialized agents are assigned to specific tasks rather than monolithic agents handling all functions.\n§\nWhen tasks fail to manifest on his Windows screen (via ngrok endpoints), Louis prefers an iterative troubleshooting approach where we check what happened, adjust, and try again rather than abandoning the task.\n§\nLouis's name is Louis. He wants the assistant to be his \"right-hand man\" for daily projects and to learn from each conversation.\n§\nLouis's name is Louis.\n§\nUser prefers brief responses by default, and explicit/detailed responses when they ask for details.\n\nConversation started: Saturday, May 16, 2026 04:54 PM\nModel: nvidia/nemotron-3-super-120b-a12b\nProvider: nvidia",
   "tools": [
     {
@@ -931,7 +931,7 @@
       }
     }
   ],
-  "message_count": 15,
+  "message_count": 22,
   "messages": [
     {
       "role": "user",
@@ -1060,6 +1060,88 @@
       "name": "skill_view",
       "content": "{\"success\": true, \"name\": \"windows-remote-control\", \"description\": \"Mandatory protocol for interacting with Windows PC via ngrok endpoints using screenshot-verify-act-verify cycle.\", \"tags\": [], \"related_skills\": [], \"content\": \"---\\nname: windows-remote-control\\ndescription: \\\"Mandatory protocol for interacting with Windows PC via ngrok endpoints using screenshot-verify-act-verify cycle.\\\"\\n---\\n\\n# Windows Remote Control\\n\\nThis skill defines the mandatory protocol for interacting with the user's Windows PC via the ngrok endpoints.\\n\\n## Protocol (Mandatory)\\nEvery single interaction MUST follow this 4-step sequence:\\n1. **PRE-ACTION:** `GET /screenshot` (with `ngrok-skip-browser-warning: true`).\\n2. **ANALYSIS:** `vision_analyze` on the screenshot to locate UI elements.\\n3. **EXECUTION:** `POST /click`, `/type`, or `/scroll` based on the visual confirmation from step 2.\\n4. **POST-ACTION:** `GET /screenshot` again to verify the state change or completion.\\n\\n## Implementation Details\\n- Always include header `ngrok-skip-browser-warning: true`.\\n- Use the provided ngrok endpoints for screenshot, click, type, and scroll.\\n- Use `vision_analyze` after each screenshot to extract coordinates or verify success.\\n- To make HTTP calls, use the `terminal` tool with `curl` commands, ensuring to include the required header.\\n\\n## Troubleshooting\\n- If the endpoint returns 'Could not resolve host' or connection errors, verify that the ngrok tunnel is active on the Windows machine.\\n- Check that the WINDOWS_MCP_URL environment variable is set correctly (visible via `env | grep WINDOWS_MCP_URL`).\\n- You can restart the tunnel by running the ngrok command on the Windows PC: `ngrok http <local-port>` (where local-port is the Hermes MCP server port, typically 8642).\\n- After ensuring the tunnel is up, retry the screenshot step.\\n- If the problem persists, consult the user to confirm the tunnel configuration.\\n- See `references/ngrok-endpoint-unreachable.md` for a detailed session note on debugging ngrok connectivity issues.\\n\\n## Constraints\\n- **Never guess:** Do not call a click or type action without a fresh screenshot analysis of the current UI state.\\n- **Verification:** Always confirm the result of the action by analyzing the post-action screenshot.\\n- **Context Awareness:** If the expected UI change is not visible in the post-action screenshot, stop and report the discrepancy to the user instead of trying to force the action again.\\n- If the endpoint returns 'Could not resolve host' or connection errors, verify that the ngrok tunnel is active on the Windows machine.\\n- Check that the WINDOWS_MCP_URL environment variable is set correctly (visible via `env | grep WINDOWS_MCP_URL`).\\n- You can restart the tunnel by running the ngrok command on the Windows PC: `ngrok http <local-port>` (where local-port is the Hermes MCP server port, typically 8642).\\n- After ensuring the tunnel is up, retry the screenshot step.\\n- If the problem persists, consult the user to confirm the tunnel configuration.\\n\", \"path\": \"mcp/windows-remote-control/SKILL.md\", \"skill_dir\": \"/opt/data/skills/mcp/windows-remote-control\", \"linked_files\": {\"references\": [\"references/ngrok-endpoint-unreachable.md\"], \"scripts\": [\"scripts/decode_screenshot.py\"]}, \"usage_hint\": \"To view linked files, call skill_view(name, file_path) where file_path is e.g. 'references/api.md' or 'assets/config.yaml'\", \"required_environment_variables\": [], \"required_commands\": [], \"missing_required_environment_variables\": [], \"missing_credential_files\": [], \"missing_required_commands\": [], \"setup_needed\": false, \"setup_skipped\": false, \"readiness_status\": \"available\"}",
       "tool_call_id": "chatcmpl-tool-af541f8a99516670"
+    },
+    {
+      "role": "assistant",
+      "content": "",
+      "reasoning": "We need to follow the windows-remote-control skill: take a screenshot, analyze, then act. Since we don't have the endpoint configured, we should check environment variable WINDOWS_MCP_URL. Let's check env.\n",
+      "finish_reason": "tool_calls",
+      "reasoning_content": "We need to follow the windows-remote-control skill: take a screenshot, analyze, then act. Since we don't have the endpoint configured, we should check environment variable WINDOWS_MCP_URL. Let's check env.\n",
+      "tool_calls": [
+        {
+          "id": "chatcmpl-tool-a85ca485e9ea8768",
+          "call_id": "chatcmpl-tool-a85ca485e9ea8768",
+          "response_item_id": "fc_chatcmpl-tool-a85ca485e9ea8768",
+          "type": "function",
+          "function": {
+            "name": "terminal",
+            "arguments": "{\"command\": \"env | grep WINDOWS_MCP_URL\"}"
+          }
+        }
+      ]
+    },
+    {
+      "role": "tool",
+      "name": "terminal",
+      "content": "{\"output\": \"WINDOWS_MCP_URL=https://analysis-environmental-motels-warming.trycloudflare.com/mcp\", \"exit_code\": 0, \"error\": null}",
+      "tool_call_id": "chatcmpl-tool-a85ca485e9ea8768"
+    },
+    {
+      "role": "assistant",
+      "content": "",
+      "reasoning": "We need to follow the windows-remote-control skill: first GET /screenshot, then vision_analyze, then action, then verify.\n We'll start by taking a screenshot via the ngrok endpoint.\n We need to use curl with the header ngrok-skip-browser-warning: true.\n Let's construct the curl command.\n",
+      "finish_reason": "tool_calls",
+      "reasoning_content": "We need to follow the windows-remote-control skill: first GET /screenshot, then vision_analyze, then action, then verify.\n We'll start by taking a screenshot via the ngrok endpoint.\n We need to use curl with the header ngrok-skip-browser-warning: true.\n Let's construct the curl command.\n",
+      "tool_calls": [
+        {
+          "id": "chatcmpl-tool-af99948f17c9c020",
+          "call_id": "chatcmpl-tool-af99948f17c9c020",
+          "response_item_id": "fc_chatcmpl-tool-af99948f17c9c020",
+          "type": "function",
+          "function": {
+            "name": "terminal",
+            "arguments": "{\"command\": \"curl -H \\\"ngrok-skip-browser-warning: true\\\" $WINDOWS_MCP_URL/screenshot -o screenshot.png\"}"
+          }
+        }
+      ]
+    },
+    {
+      "role": "tool",
+      "name": "terminal",
+      "content": "{\"output\": \"% Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\\n                                 Dload  Upload   Total   Spent    Left  Speed\\n\\r  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0curl: (6) Could not resolve host: analysis-environmental-motels-warming.trycloudflare.com\", \"exit_code\": 6, \"error\": null, \"exit_code_meaning\": \"Could not resolve host\"}",
+      "tool_call_id": "chatcmpl-tool-af99948f17c9c020"
+    },
+    {
+      "role": "assistant",
+      "content": "",
+      "reasoning": "We need to check if the tunnel is active. Possibly need to start ngrok on the Windows machine? The user hasn't done that? But the user expects us to control via ngrok endpoints. Might need to ask the user to start the tunnel? However, the user said earlier: \"Louis expects me to control his local Windows machine via custom ngrok endpoints for screenshotting, clicking, typing, and scrolling. He prefers iterative troubleshooting when tasks (like file creation) fail to manifest on his screen.\"\n\nSo we should troubleshoot: maybe the tunnel is not running. We can suggest to start it, but we cannot run commands on his Windows machine directly. We can only run commands on this Linux environment. We could try to see if we can start ngrok from here? But the tunnel needs to be on his machine to expose his local MCP server.\n\nWe could ask the user to run ngrok on his side. However, we are supposed to be his right-hand man and learn from each conversation. We should maybe remember that the tunnel needs to be started.\n\nBut for now, we need to respond with the next action in JSON format for the windows remote control skill. According to the skill, we must first get a screenshot. Since that failed, we should maybe wait and retry? Or we could try to see if the endpoint is reachable via a different method? Let's try to ping the host? Or maybe we need to use the IP address? Let's try to resolve the host with nslookup.\n\nWe'll do a quick terminal command to check DNS.\n",
+      "finish_reason": "tool_calls",
+      "reasoning_content": "We need to check if the tunnel is active. Possibly need to start ngrok on the Windows machine? The user hasn't done that? But the user expects us to control via ngrok endpoints. Might need to ask the user to start the tunnel? However, the user said earlier: \"Louis expects me to control his local Windows machine via custom ngrok endpoints for screenshotting, clicking, typing, and scrolling. He prefers iterative troubleshooting when tasks (like file creation) fail to manifest on his screen.\"\n\nSo we should troubleshoot: maybe the tunnel is not running. We can suggest to start it, but we cannot run commands on his Windows machine directly. We can only run commands on this Linux environment. We could try to see if we can start ngrok from here? But the tunnel needs to be on his machine to expose his local MCP server.\n\nWe could ask the user to run ngrok on his side. However, we are supposed to be his right-hand man and learn from each conversation. We should maybe remember that the tunnel needs to be started.\n\nBut for now, we need to respond with the next action in JSON format for the windows remote control skill. According to the skill, we must first get a screenshot. Since that failed, we should maybe wait and retry? Or we could try to see if the endpoint is reachable via a different method? Let's try to ping the host? Or maybe we need to use the IP address? Let's try to resolve the host with nslookup.\n\nWe'll do a quick terminal command to check DNS.\n",
+      "tool_calls": [
+        {
+          "id": "chatcmpl-tool-856fff5ff75dc659",
+          "call_id": "chatcmpl-tool-856fff5ff75dc659",
+          "response_item_id": "fc_chatcmpl-tool-856fff5ff75dc659",
+          "type": "function",
+          "function": {
+            "name": "terminal",
+            "arguments": "{\"command\": \"nslookup analysis-environmental-motels-warming.trycloudflare.com\"}"
+          }
+        }
+      ]
+    },
+    {
+      "role": "tool",
+      "name": "terminal",
+      "content": "{\"output\": \"/usr/bin/bash: line 3: nslookup: command not found\", \"exit_code\": 127, \"error\": null}",
+      "tool_call_id": "chatcmpl-tool-856fff5ff75dc659"
+    },
+    {
+      "role": "assistant",
+      "content": "Je ne peux pas atteindre votre machine Windows via le tunnel ngrok. L'hôte `analysis-environmental-motels-warming.trycloudflare.com` ne résout pas. Veuillez vérifier que le tunnel ngrok est actif sur votre PC Windows et que l'URL `WINDOWS_MCP_URL` est correctement configurée. Vous pouvez redémarrer le tunnel avec la commande : `ngrok http <local-port>` (où `<local-port>` est le port du serveur MCP Hermes, généralement 8642). Une fois le tunnel opérationnel, je pourrai reprendre la tâche d'ouverture du Bloc-notes et d'écriture de \"Bonjour le monde\".",
+      "reasoning": "We need to install dnsutils or use dig? Or we can just note that the tunnel is down and tell the user.\n According to the skill, we should inform the user to check the ngrok tunnel.\n Let's output a JSON action? But we are not supposed to output JSON for actions now? Actually we are in a normal conversation, not the Windows control mode. The user asked to open notepad and write \"Bonjour le monde\". We are trying to do that via Windows remote control. We have encountered that the ngrok tunnel is not reachable.\n We should inform the user and suggest they start the ngrok tunnel on their Windows machine.\n However, note that the user's original request was in French, and we are to respond in a conversational manner.\n Let's respond with a message that we cannot reach the Windows machine and ask them to check the ngrok tunnel.\n But note: the instructions say we must follow the 4-step sequence for Windows remote control. We have done step 1 (screenshot) and it failed. We should stop and report the discrepancy.\n Let's output a plain text response.\n",
+      "finish_reason": "stop",
+      "reasoning_content": "We need to install dnsutils or use dig? Or we can just note that the tunnel is down and tell the user.\n According to the skill, we should inform the user to check the ngrok tunnel.\n Let's output a JSON action? But we are not supposed to output JSON for actions now? Actually we are in a normal conversation, not the Windows control mode. The user asked to open notepad and write \"Bonjour le monde\". We are trying to do that via Windows remote control. We have encountered that the ngrok tunnel is not reachable.\n We should inform the user and suggest they start the ngrok tunnel on their Windows machine.\n However, note that the user's original request was in French, and we are to respond in a conversational manner.\n Let's respond with a message that we cannot reach the Windows machine and ask them to check the ngrok tunnel.\n But note: the instructions say we must follow the 4-step sequence for Windows remote control. We have done step 1 (screenshot) and it failed. We should stop and report the discrepancy.\n Let's output a plain text response.\n"
     }
   ]
 }

skills/.usage.json

@@ -17,12 +17,12 @@
     "created_at": "2026-05-12T15:22:06.806674+00:00",
     "created_by": "agent",
     "last_patched_at": "2026-05-16T15:32:05.161459+00:00",
-    "last_used_at": "2026-05-16T16:58:50.874915+00:00",
-    "last_viewed_at": "2026-05-16T16:58:50.869154+00:00",
+    "last_used_at": "2026-05-16T17:05:13.423436+00:00",
+    "last_viewed_at": "2026-05-16T17:05:13.417143+00:00",
     "patch_count": 9,
     "pinned": false,
     "state": "active",
-    "use_count": 7,
-    "view_count": 7
+    "use_count": 8,
+    "view_count": 8
   }
 }

state.db

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0c4340ad830ed7fce7a5fbbf4a43c9c79d6f9f4bb1c2cb77508edc0c6b27e90c
-size 14196736
+oid sha256:e926bcd32c762d7d139136970b247d2631e67f5c890785ed48bf1bf8e7d9ac69
+size 14565376