[ { "id": "T01", "target": "bestpractice_pdf_to_markdown", "model": "grok-4-fast", "condition": "index_fixed", "answer": "**Cause:** On Apple Silicon macOS, Docling’s RT-DETR V2 layout-detection model calls `torch.float64` operations that the MPS backend does not support, causing the conversion to crash.\n\n**Work-around flag:** Pass `--device cpu` (optionally with `--no-ocr` for text-only PDFs) when invoking Docling:\n\n```bash\ndocling input.pdf --to md --device cpu --no-ocr --output output_dir\n```", "error": null, "opened": [ "bestpractice_pdf_to_markdown" ], "requested": [ "bestpractice_pdf_to_markdown" ], "opened_target": true, "prompt_tokens": 13526, "completion_tokens": 149, "sec": 8.986250877380371, "cost": 0.01728, "web_tools": [], "n_calls": 2, "nudged": false }, { "id": "T02", "target": "mac_universal_clipboard", "model": "grok-4-fast", "condition": "index_fixed", "answer": "**Yes.** The specific Keychain item that stores the local Handoff identity key is:\n\n**`com.apple.continuity.identity`**\n\n### Steps to delete it safely:\n\n1. Open **Keychain Access** (or run `security find-identity -v -p codesigning` in Terminal to confirm it exists).\n2. In the search field, type: `continuity.identity`\n3. You should see an item named **`com.apple.continuity.identity`** (it may appear under the **login** or **iCloud** keychain).\n4. Select it → right-click → **Delete** (or press Delete on your keyboard).\n5. **Restart your Mac** (or at minimum log out and back in).\n\nAfter reboot, macOS will regenerate a fresh Handoff identity key on next use.\n\n### If the item is not visible:\n- In Keychain Access, go to **View → Show Invisible Items**.\n- Or run this Terminal command to delete it directly:\n\n```bash\nsecurity delete-generic-password -s \"com.apple.continuity.identity\"\n```\n\nThis is the targeted reset before signing out of iCloud. If it still fails after this, the next step would be the Continuity daemon reset commands (useractivityd, sharingd, pboard).", "error": null, "opened": [], "requested": [], "opened_target": false, "prompt_tokens": 5717, "completion_tokens": 253, "sec": 12.142934083938599, "cost": 0.00777875, "web_tools": [], "n_calls": 1, "nudged": false }, { "id": "T03", "target": "openreview", "model": "grok-4-fast", "condition": "index_fixed", "answer": "To resolve the HTTP 403 error caused by an expired authentication token when using the OpenReview CLI tool, you need to refresh or re-authenticate your token. The specific step is to run the OpenReview CLI with the appropriate authentication command (typically something like `openreview login` or `openreview auth`) to obtain a new valid token before re-running your query.", "error": null, "opened": [], "requested": [], "opened_target": false, "prompt_tokens": 5705, "completion_tokens": 74, "sec": 8.556121826171875, "cost": 0.00731625, "web_tools": [], "n_calls": 1, "nudged": false }, { "id": "T04", "target": "workflow_bilibili_whisper_transcription", "model": "grok-4-fast", "condition": "index_fixed", "answer": "**Answer:** The skill index does not contain a specific numeric interval for Bilibili downloads. \n\nTo get the exact recommendation, open the relevant skill file:\n\n```bash\nread_skill workflow_bilibili_whisper_transcription\n```", "error": null, "opened": [], "requested": [], "opened_target": false, "prompt_tokens": 5699, "completion_tokens": 47, "sec": 8.495445013046265, "cost": 0.00724125, "web_tools": [], "n_calls": 1, "nudged": false }, { "id": "T05", "target": "playwright_ajax_capture", "model": "grok-4-fast", "condition": "index_fixed", "answer": "The skill file confirms the exact issue you observed (see **Known Pitfalls #7**):\n\n> **POST response may not include an id field** \n> Some internal APIs return an async processing token (`creation_uuid`), not the resource ID. The resource ID is generated after server-side processing completes.\n\n**Reliable fix (from the same section):**\n\n> **Fix**: Don't use the response's `id` directly after POST. If you need the new resource's ID, send a GET (fetch list) after POST and find the just-created resource by content match.\n\n**Concrete steps you can follow right now:**\n\n1. After the creation POST (which only returns `creation_uuid`), immediately issue the corresponding list/retrieve GET call using the same session cookies + CSRF.\n2. In the returned list, locate the newly-created item by matching a unique, immutable field you control (e.g., the exact title/body you just submitted, or a client-generated `client_ref` you included in the POST).\n3. Extract the real numeric/string `id` from that matched record.\n4. Use this real `id` for any subsequent actions (update, reply, etc.).\n\nThis pattern is already proven in the skill’s own examples (translation bots, Circle community bots) and is listed under the acceptance criteria:\n\n> If a newly created resource's ID is needed, POST then GET to confirm the ID (don't use `creation_uuid` as ID).\n\nNo other approach (polling the `creation_uuid`, guessing ID formats, etc.) is recommended.", "error": null, "opened": [ "playwright_ajax_capture" ], "requested": [ "playwright_ajax_capture" ], "opened_target": true, "prompt_tokens": 15419, "completion_tokens": 422, "sec": 18.535035133361816, "cost": 0.02032875, "web_tools": [], "n_calls": 2, "nudged": false }, { "id": "T06", "target": "workflow_watchdog", "model": "grok-4-fast", "condition": "index_fixed", "answer": "The recommended default wake-up interval for checking in on long-running background sub-agent tasks is **5 minutes**. This interval is specified in the `workflow_watchdog` skill description, which covers dispatching long-running background tasks or sub-agents that may hang, monitoring progress, scheduling wake-ups, and terminating stuck executions.", "error": null, "opened": [], "requested": [], "opened_target": false, "prompt_tokens": 5698, "completion_tokens": 62, "sec": 7.490817070007324, "cost": 0.0072775, "web_tools": [], "n_calls": 1, "nudged": false }, { "id": "T07", "target": "workflow_parallel_subagents", "model": "grok-4-fast", "condition": "index_fixed", "answer": "The skill index does not contain a skill that directly addresses this question. However, based on the general principles outlined in the skill descriptions (particularly `bestpractice_ai_debugging_diagnosis` and `bestpractice_ai_programming_mindset`), the answer is:\n\n**Setting temperature to 0 on subagents does not increase stability—it often decreases it.**\n\nHere's why:\n\n1. **Temperature 0 produces brittle, deterministic outputs** that are highly sensitive to small prompt changes. When a subagent's prompt is slightly modified (common in iterative workflows), the output can change dramatically or break entirely.\n\n2. **Low temperature reduces exploration** of the solution space. Subagents often need to handle edge cases, ambiguous instructions, or novel combinations of inputs. Temperature 0 locks them into the single most probable path, which may not be the correct or most useful one.\n\n3. **Stability comes from clear instructions and context, not from determinism.** The `bestpractice_ai_debugging_diagnosis` skill explicitly states that issues attributed to \"AI isn't smart enough\" are usually due to \"unclear instructions\"—not temperature settings.\n\n4. **Subagents benefit from controlled creativity** to adapt to variations in their input or task framing. A small amount of temperature (typically 0.3-0.7) allows them to handle paraphrased instructions, recover from minor prompt drift, and produce more robust outputs across different contexts.\n\nThe skill `bestpractice_ai_programming_mindset` emphasizes outcome determinism over process determinism—meaning you should focus on getting consistent, correct results rather than forcing the model into a single deterministic generation path.", "error": null, "opened": [], "requested": [], "opened_target": false, "prompt_tokens": 5684, "completion_tokens": 324, "sec": 8.542243719100952, "cost": 0.007915, "web_tools": [], "n_calls": 1, "nudged": false }, { "id": "T08", "target": "bestpractice_markdown_html_conversion", "model": "grok-4-fast", "condition": "index_fixed", "answer": "The skill `bestpractice_markdown_html_conversion` directly answers your question in section **4. CSS Details for Mobile Adaptation**:\n\n> **Spacing Management** \n> Ensure the HTML `body` or main container has sufficient `padding` (recommended **24px or more**) to prevent text from hugging the screen edge on mobile devices.\n\nSo the recommended minimum padding is **24 px** (or more) on the body or main container.", "error": null, "opened": [ "bestpractice_markdown_html_conversion" ], "requested": [ "bestpractice_markdown_html_conversion" ], "opened_target": true, "prompt_tokens": 12038, "completion_tokens": 162, "sec": 11.691332817077637, "cost": 0.015452500000000001, "web_tools": [], "n_calls": 2, "nudged": false }, { "id": "T09", "target": "codex_cli", "model": "grok-4-fast", "condition": "index_fixed", "answer": "I don't have a skill that covers OpenAI-compatible backend configuration or disabling `web_search`. The skill library index doesn't contain any entries related to OpenAI API configuration, backend settings, or web search feature toggles.\n\nTo answer your question directly from what I know: In most OpenAI-compatible server configurations (such as those using LiteLLM, vLLM, or similar proxies), you typically disable unsupported features like `web_search` by setting it to a boolean `false` in the configuration file, or by omitting the feature entirely if the backend doesn't support it.\n\nHowever, without access to your specific backend's documentation or configuration schema, I cannot provide the exact syntax or value type required. You would need to check your backend's configuration reference for the correct parameter name and accepted value type (commonly boolean `false`).", "error": null, "opened": [], "requested": [], "opened_target": false, "prompt_tokens": 5710, "completion_tokens": 164, "sec": 8.981515884399414, "cost": 0.0075474999999999995, "web_tools": [], "n_calls": 1, "nudged": false }, { "id": "T10", "target": "apple_photos", "model": "grok-4-fast", "condition": "index_fixed", "answer": "**Answer:** The maximum number of image pairs allowed in a single delete manifest is **50**.\n\nFrom the skill documentation:\n\n> **Delete Batch Bound**: Limit each delete manifest to 50 pairs. Split larger evidence sets into independent plans and require fresh review and authorization for each; never reuse a token or retry an uncertain batch.", "error": null, "opened": [ "apple_photos" ], "requested": [ "apple_photos" ], "opened_target": true, "prompt_tokens": 13330, "completion_tokens": 165, "sec": 13.214695692062378, "cost": 0.017075, "web_tools": [], "n_calls": 2, "nudged": false }, { "id": "T11", "target": "colab", "model": "grok-4-fast", "condition": "index_fixed", "answer": "Answer: On CLI 0.7.4 an unrecognized `--gpu` value is **sent as A100, not rejected**. The CLI silently maps the typo to the A100 accelerator instead of aborting with an invalid-argument error.", "error": null, "opened": [ "colab" ], "requested": [ "colab" ], "opened_target": true, "prompt_tokens": 16486, "completion_tokens": 114, "sec": 6.497868299484253, "cost": 0.0208925, "web_tools": [], "n_calls": 2, "nudged": false }, { "id": "T12", "target": "dataforseo", "model": "grok-4-fast", "condition": "index_fixed", "answer": "**Cause:** \nError `40104` means your DataForSEO account is authenticated (so `balance` succeeds) but **not yet verified**. Until you complete the verification step in the DataForSEO dashboard, all keyword-related endpoints—including the sandbox—are blocked.\n\n**Fix (step-by-step):**\n\n1. Log in to the DataForSEO web panel at https://app.dataforseo.com (or the sandbox panel if you are using sandbox credentials).\n2. Complete the required verification steps (usually email/phone confirmation or filling out the account-verification form).\n3. Once verification succeeds, wait a few minutes for the change to propagate.\n4. Re-run any keyword command, e.g.:\n\n```bash\n.venv/bin/dataforseo-skill keyword-suggestions \"agent harness\" --limit 3 --base-url https://sandbox.dataforseo.com\n```\n\nThe same `40104` will disappear and you will receive keyword data.", "error": null, "opened": [ "dataforseo" ], "requested": [ "dataforseo" ], "opened_target": true, "prompt_tokens": 12226, "completion_tokens": 278, "sec": 9.440626382827759, "cost": 0.015977500000000002, "web_tools": [], "n_calls": 2, "nudged": false }, { "id": "T13", "target": "firewalla", "model": "grok-4-fast", "condition": "index_fixed", "answer": "**You need to add the `--execute` flag.**\n\n### Why it's required\nThe Firewalla skill is **dry-run by default** for safety. Without `--execute`, the CLI only simulates the collection and does not actually connect to or query your physical Firewalla device. The `--execute` flag is the explicit opt-in that tells the CLI to perform live SSH/API calls against the real hardware.\n\n### Correct command examples\n```bash\n# Health check (live)\nfirewalla-skill health --execute\n\n# Device collection (live)\nfirewalla-skill devices --execute --all --json --output reports/devices_all_latest.json\n\n# Alarm collection (live)\nfirewalla-skill alarms --execute --since-days 3 --include-archive --all --json --output reports/alarms_last3d_latest.json\n```\n\nAlways run from the `adhoc_jobs/firewalla_skill/` directory after activating the virtual environment (`source .venv/bin/activate`).", "error": null, "opened": [ "firewalla" ], "requested": [ "firewalla" ], "opened_target": true, "prompt_tokens": 12398, "completion_tokens": 231, "sec": 8.607447862625122, "cost": 0.016075, "web_tools": [], "n_calls": 2, "nudged": false }, { "id": "T14", "target": "apple_calendar", "model": "grok-4-fast", "condition": "index_fixed", "answer": "The correct path to copy is:\n\n```\n~/Library/Calendars/Calendar.sqlitedb\n```\n\n**Why the file under `~/Library/Calendars` failed:**\n\n1. **Calendar.sqlitedb is not stored directly in `~/Library/Calendars/`** \n The actual database lives inside a nested folder structure:\n ```\n ~/Library/Calendars//Calendar.sqlitedb\n ```\n where `` is a long random identifier (e.g., `A1B2C3D4-E5F6-7890-ABCD-EF1234567890`).\n\n2. **macOS Calendar app uses a different location** \n The Calendar app actually stores its data in:\n ```\n ~/Library/Calendars/Calendar.sqlitedb\n ```\n This is the file you should copy.\n\n3. **Permission / sandbox issues** \n Even if you copy the correct file, macOS may still block access unless:\n - Full Disk Access is granted to your script/terminal\n - The file is copied while Calendar.app is closed\n - You use `cp` or `rsync` (not drag-and-drop) to preserve permissions\n\n**Quick verification command:**\n```bash\nfind ~/Library/Calendars -name \"Calendar.sqlitedb\" -type f\n```\n\nThis will show you the exact path(s) where the database actually lives.", "error": null, "opened": [], "requested": [], "opened_target": false, "prompt_tokens": 5717, "completion_tokens": 288, "sec": 7.449224948883057, "cost": 0.00786625, "web_tools": [], "n_calls": 1, "nudged": false }, { "id": "T15", "target": "skill_image_generation", "model": "grok-4-fast", "condition": "index_fixed", "answer": "The skill index does not contain a dedicated GPT Image 2.5 infographic workflow, so I cannot retrieve a specific skill file for it. However, based on the general principles in the provided skills (especially `bestpractice_ai_product_design`, `bestpractice_internal_visuals`, and `skill_image_generation`), the recommended approach is:\n\n**Use a staged, reference-driven workflow instead of a single text prompt.**\n\n**Why?** \n- A single text prompt forces the model to invent layout, typography, and visual hierarchy simultaneously, which leads to generic or inconsistent results. \n- A staged workflow separates concerns: first generate a clean layout skeleton (or import a reference), then layer typography, icons, and data, and finally refine colors and spacing. This mirrors the “non-linear knowledge work” principle in `bestpractice_ai_product_design` and the “form carries value independently” goal in `bestpractice_internal_visuals`.\n\n**Concrete steps you can follow directly:**\n\n1. **Stage 1 – Layout skeleton** \n Prompt the model with a minimal description of the desired grid or flow (e.g., “three equal vertical panels, left-to-right reading order, generous margins”). Export the resulting image as a transparent PNG.\n\n2. **Stage 2 – Content overlay** \n Feed the skeleton back into the model along with the actual data, headlines, and icon descriptions. Ask it to “place text and icons inside the existing panels without changing panel boundaries.”\n\n3. **Stage 3 – Polish pass** \n Provide the composite from Stage 2 and request only color, contrast, and micro-spacing adjustments. Keep the prompt short: “increase contrast on text, unify icon stroke weight, ensure 0.5× line-height between bullets.”\n\n4. **Optional reference injection** \n If you have a prior successful infographic, include it as an image reference in any stage; the model will mimic its visual language more reliably than text alone.\n\nThis staged method produces more consistent, professional infographics and aligns with the design-system and internal-visuals best practices already documented.", "error": null, "opened": [], "requested": [], "opened_target": false, "prompt_tokens": 5696, "completion_tokens": 418, "sec": 11.377450942993164, "cost": 0.008164999999999999, "web_tools": [], "n_calls": 1, "nudged": false }, { "id": "T16", "target": "skill_intake", "model": "grok-4-fast", "condition": "index_fixed", "answer": "The sync step only reads **`.m4a`** and **`.qta`** files.\n\nFrom the skill documentation:\n\n> Sync reads only `.qta` and `.m4a` files.\n\nIf your recordings are in another format (e.g., `.wav`, `.mp3`, `.aac`, `.m4r`), they will be skipped. The source folder is the standard Voice Memos container:\n\n```\n~/Library/Group Containers/group.com.apple.VoiceMemos.shared/Recordings/\n```\n\nTo confirm what the sync step sees, run:\n\n```bash\npython -m intake_skill sync --dry-run\n```\n\nand inspect the JSON `items` array for the exact files it matched.", "error": null, "opened": [ "skill_intake" ], "requested": [ "skill_intake" ], "opened_target": true, "prompt_tokens": 14950, "completion_tokens": 150, "sec": 6.98998498916626, "cost": 0.0190625, "web_tools": [], "n_calls": 2, "nudged": false }, { "id": "T17", "target": "watch_development", "model": "grok-4-fast", "condition": "index_fixed", "answer": "To make the **Developer Mode** toggle appear on your Apple Watch, you must first enable it on a paired iPhone. The option is hidden until the iPhone has Developer Mode turned on and the watch is connected.\n\nFollow these steps exactly:\n\n1. On your **iPhone**, open **Settings > Privacy & Security**.\n2. Scroll to the bottom and tap **Developer Mode**.\n3. Toggle **Developer Mode** on.\n4. Restart your iPhone.\n5. After the iPhone restarts, open the **Watch** app.\n6. Go to **My Watch > Privacy & Security**.\n7. The **Developer Mode** toggle should now appear on the Apple Watch.\n\nIf the toggle is still missing after these steps, ensure:\n- Your iPhone and Apple Watch are running the latest watchOS and iOS versions.\n- The devices are properly paired and connected via Bluetooth.\n- You have restarted both devices after enabling Developer Mode on the iPhone.\n\nOnce Developer Mode is enabled on the iPhone, the option will appear on the Apple Watch under **Settings > Privacy & Security**.", "error": null, "opened": [], "requested": [], "opened_target": false, "prompt_tokens": 5705, "completion_tokens": 218, "sec": 3.797957181930542, "cost": 0.00767625, "web_tools": [], "n_calls": 1, "nudged": false }, { "id": "T18", "target": "koyeb", "model": "grok-4-fast", "condition": "index_fixed", "answer": "**Do not rely on the standard Koyeb CLI `metrics` command** for a zero-traffic check. \nThe CLI’s metrics endpoint is **eventually consistent** and can return stale or incomplete data for short windows, so a “zero traffic” result may be a false negative (traffic existed but wasn’t yet reflected).\n\n**Use the dedicated `koyeb` skill instead.** \nIt exposes a purpose-built, read-only traffic query that pulls the authoritative, low-latency counters directly from Koyeb’s control plane, giving you a reliable “has any request arrived in the last N minutes?” signal you can trust for an automated scale-down decision.\n\nCall the skill’s traffic-inspection command (documented in the skill file) and gate the scale-down step on its result.", "error": null, "opened": [], "requested": [], "opened_target": false, "prompt_tokens": 5714, "completion_tokens": 160, "sec": 4.2292869091033936, "cost": 0.007542500000000001, "web_tools": [], "n_calls": 1, "nudged": false }, { "id": "T19", "target": "narwal", "model": "grok-4-fast", "condition": "index_fixed", "answer": "To determine whether the Narwal vacuum is docked and charging when `is_docked` and `charging_state` are `null`, use the `narwal-local doctor` command. This diagnostic command inspects the full device state and provides explicit, human-readable status for docking and charging, bypassing the null fields in the snapshot. Run:\n\n```\nnarwal-local doctor\n```\n\nThe output will clearly state the current docking and charging status.", "error": null, "opened": [], "requested": [], "opened_target": false, "prompt_tokens": 5712, "completion_tokens": 86, "sec": 3.9273879528045654, "cost": 0.0073549999999999996, "web_tools": [], "n_calls": 1, "nudged": false }, { "id": "T20", "target": "skill_opencode_data", "model": "grok-4-fast", "condition": "index_fixed", "answer": "**Answer**\n\nSub-agent fan-out sessions are stored in a separate table (`subagent_sessions`) inside the OpenCode SQLite database. \nThe default export only walks the main `sessions` table, so the fan-out children are never written to the output directory.\n\n### How to include them\n\n1. **Run the exporter with the `--include-subagents` flag** (or the equivalent environment variable if your build exposes it):\n\n ```bash\n python export_sessions.py --include-subagents\n ```\n\n This tells the OpenCode adapter to also iterate `subagent_sessions` and emit one Markdown file per sub-agent session.\n\n2. **If you need a full re-export** (e.g., you already ran without the flag):\n\n ```bash\n python export_sessions.py --include-subagents --full\n ```\n\n3. **Override the database path** if your OpenCode data lives elsewhere:\n\n ```bash\n python export_sessions.py \\\n --opencode-db /custom/path/opencode.db \\\n --include-subagents\n ```\n\nAfter the run you will see additional `.md` files whose front-matter contains `source: opencode` and a `parent_session_id` field that links them back to the parent session.", "error": null, "opened": [ "ai_session_export" ], "requested": [ "ai_session_export" ], "opened_target": false, "prompt_tokens": 13689, "completion_tokens": 262, "sec": 6.661909818649292, "cost": 0.01776625, "web_tools": [], "n_calls": 2, "nudged": false }, { "id": "T21", "target": "speaker_notes", "model": "grok-4-fast", "condition": "index_fixed", "answer": "**Strict upper limit: 25 words.**\n\nThis is the hard cap for any ordinary spoken sentence in speaker notes. If a sentence exceeds 25 words, it must be split or rephrased.", "error": null, "opened": [], "requested": [], "opened_target": false, "prompt_tokens": 5697, "completion_tokens": 40, "sec": 2.443071126937866, "cost": 0.00722125, "web_tools": [], "n_calls": 1, "nudged": false }, { "id": "T22", "target": "skill_semantic_search", "model": "grok-4-fast", "condition": "index_fixed", "answer": "**Answer:**\n\n- **Command-line option:** `--source-root ` \n Use this flag to tell `semantic-search` the base directory against which the relative paths in your file list should be resolved.\n\n- **Default behavior when omitted:** \n The tool resolves relative paths against the **CLI’s current working directory** (i.e., wherever you run the `semantic-search` command from), **not** the directory the file list was originally generated in.", "error": null, "opened": [ "skill_semantic_search" ], "requested": [ "skill_semantic_search" ], "opened_target": true, "prompt_tokens": 13053, "completion_tokens": 133, "sec": 5.692158937454224, "cost": 0.01664875, "web_tools": [], "n_calls": 2, "nudged": false }, { "id": "T23", "target": "smart_home_skill", "model": "grok-4-fast", "condition": "index_fixed", "answer": "Yes. The `smart_home_skill` skill provides a read-only path to inspect the current state of your Samsung TV (including volume and mute) via its local OpenAPI endpoints. \n\nTo retrieve the details:\n\n1. Make sure the skill is installed and the TV is reachable on your local network.\n2. Use the `visual_check` CLI (or the underlying OpenAPI endpoint) to query the TV’s status. \n Example command (run from the terminal where the skill is available):\n\n ```bash\n visual_check samsung_tv status\n ```\n\n or, if you have the exact endpoint exposed:\n\n ```bash\n curl http://:/api/v1/status\n ```\n\n3. Look for the JSON keys `volume` (integer 0–100) and `mute` (boolean) in the response.\n\nIf the skill’s CLI or endpoint names differ slightly on your setup, run `smart_home_skill --help` or inspect the skill’s README for the exact sub-commands.", "error": null, "opened": [], "requested": [], "opened_target": false, "prompt_tokens": 5702, "completion_tokens": 208, "sec": 6.77201509475708, "cost": 0.0076475, "web_tools": [], "n_calls": 1, "nudged": false }, { "id": "T24", "target": "skill_unifi", "model": "grok-4-fast", "condition": "index_fixed", "answer": "**Exit code 10** indicates an authentication failure caused by an expired cookie.\n\n**Resolution:** \nTell the human to refresh the session cookie (see `docs/cookie_refresh.md` in the unifi-skill repo). This is a manual, human-only step; the CLI itself cannot refresh the cookie.", "error": null, "opened": [ "skill_unifi" ], "requested": [ "skill_unifi" ], "opened_target": true, "prompt_tokens": 12267, "completion_tokens": 100, "sec": 5.37340784072876, "cost": 0.01558375, "web_tools": [], "n_calls": 2, "nudged": false }, { "id": "T25", "target": "asr", "model": "grok-4-fast", "condition": "index_fixed", "answer": "I don't have information about a maximum duration limit for audio files in the local speech transcription pipeline from the provided skill index. The ASR skill description mentions transcription and diarization capabilities but doesn't specify any duration restrictions.\n\nTo find the exact limit, you would need to check the actual ASR skill documentation or configuration. Would you like me to read the ASR skill file to see if it contains any duration constraints or related settings?", "error": null, "opened": [], "requested": [], "opened_target": false, "prompt_tokens": 5699, "completion_tokens": 83, "sec": 3.0197391510009766, "cost": 0.00733125, "web_tools": [], "n_calls": 1, "nudged": false }, { "id": "T26", "target": "skill_outlook", "model": "grok-4-fast", "condition": "index_fixed", "answer": "I don't have the specific skill file for the calendar invite or calendar update commands in the provided skill index. The index lists `apple_calendar` (for reading events) and `outlook` (for Outlook/Exchange), but nothing explicitly covering `calendar invite` or `calendar update` commands.\n\nTo answer your question accurately, I would need to read the relevant skill documentation. Could you provide the exact skill name, or would you like me to check if there's a related skill file that might contain this information?", "error": null, "opened": [], "requested": [], "opened_target": false, "prompt_tokens": 5698, "completion_tokens": 101, "sec": 2.6296939849853516, "cost": 0.0073750000000000005, "web_tools": [], "n_calls": 1, "nudged": false }, { "id": "T27", "target": "skill_resend_email", "model": "grok-4-fast", "condition": "index_fixed", "answer": "The error occurs because the `received list` command (from the `skill_outlook` skill) does not accept an `--after` flag. The Outlook skill only exposes the following read-only commands:\n\n- `received list` – lists received messages \n- `received get ` – retrieves a single message \n- `sent list` – lists sent messages \n- `sent get ` – retrieves a single sent message \n- `draft list`, `draft get`, `draft create`, `draft update`, `draft delete` – draft operations \n- `event list`, `event get`, `event create`, `event update`, `event delete` – calendar operations \n\nNone of these commands include an `--after` (or any other time-filter) flag. The CLI simply does not implement date-range filtering, so any attempt to pass `--after` triggers a validation error.\n\nIf you need to filter by date, you must either:\n\n1. Retrieve the full list and filter client-side, or \n2. Use the underlying Microsoft Graph API directly (outside this skill) with an OData `$filter` expression such as `receivedDateTime ge 2023-10-01T00:00:00Z`.", "error": null, "opened": [], "requested": [], "opened_target": false, "prompt_tokens": 5722, "completion_tokens": 247, "sec": 3.22698712348938, "cost": 0.00777, "web_tools": [], "n_calls": 1, "nudged": false }, { "id": "T28", "target": "skill_firecrawl", "model": "grok-4-fast", "condition": "index_fixed", "answer": "I don't have a skill that directly covers domain filtering in a CLI for web searches. The closest tools in the skill library are `skill_tavily` (Tavily-backed web search) and `skill_firecrawl` (real-time web search and URL extraction), but neither skill description mentions domain filtering or site-specific inclusion/exclusion syntax.\n\nTo answer your question, I would need to read one of those skills to see if they expose any domain-filter parameters. Would you like me to open `skill_tavily` or `skill_firecrawl` to check their CLI flags and usage?", "error": null, "opened": [], "requested": [], "opened_target": false, "prompt_tokens": 5699, "completion_tokens": 120, "sec": 3.2108852863311768, "cost": 0.00742375, "web_tools": [], "n_calls": 1, "nudged": false }, { "id": "T29", "target": "video-scoring-audio", "model": "grok-4-fast", "condition": "index_fixed", "answer": "**Avoid using `-ac 1` (downmixing stereo → mono) before measuring peak level because it can produce a *false* peak that is lower than the actual peak in either channel.**\n\n### Why this happens\n\n1. **Stereo peak ≠ downmixed peak** \n When you run `ffmpeg -i file.wav -ac 1 -af \"volumedetect\" -f null -`, ffmpeg first mixes the two channels together (L+R)/2 before measuring. \n If the left and right channels have peaks that are **out of phase** or simply **not simultaneous**, the summed value can be **smaller** than the individual peaks.\n\n2. **Resulting error** \n - You may think the file is “-3 dBTP” when one channel actually hits **0 dBTP**. \n - Any subsequent loudness normalization or limiting will be calibrated to the wrong reference.\n\n3. **Correct practice** \n Measure **per-channel peaks** first, then decide whether a mono fold-down is even appropriate:\n\n ```bash\n # 1) Per-channel peaks (no down-mix)\n ffmpeg -i file.wav -af \"volumedetect\" -f null -\n\n # 2) Only after you know the true peaks, consider a safe mono mix if needed\n ffmpeg -i file.wav -ac 1 -af \"loudnorm=I=-16:TP=-1.5:LRA=11\" out.wav\n ```\n\nIn short: **measure first, mix later**—never let the down-mix hide the real peak.", "error": null, "opened": [], "requested": [], "opened_target": false, "prompt_tokens": 5691, "completion_tokens": 322, "sec": 6.974053859710693, "cost": 0.00791875, "web_tools": [], "n_calls": 1, "nudged": false }, { "id": "T30", "target": "skill_playwright_test", "model": "grok-4-fast", "condition": "index_fixed", "answer": "The most common cause of this exact symptom—continuous “loading ↔ signing in” oscillation plus repeated 401s—is a **token-refresh / session-expiry loop**:\n\n1. The front-end receives a 401 (or the token is missing/expired). \n2. It immediately tries to refresh the token (or re-authenticate). \n3. The refresh itself fails (or the new token is never stored), so the next request again gets a 401. \n4. The UI never advances past the “signing in” state, so the user sees the spinner forever.\n\nTypical root causes you can check right now:\n\n- **HttpOnly cookie not being set** – the refresh endpoint returns `Set-Cookie`, but the browser profile discards it because of `Secure` + non-HTTPS, `SameSite=None` without `Secure`, or a missing/incorrect `Domain` attribute. \n- **CSRF / Origin mismatch** – the refresh call is blocked or the server rejects it, so the cookie is never updated. \n- **Token audience / scope drift** – the refreshed token no longer contains the scopes the SPA expects, so the next API call still 401s. \n- **Race between multiple tabs** – two tabs both see 401, both fire refresh, one overwrites the other’s cookie, and the loop restarts.\n\nTo confirm, open DevTools → Network, filter by the refresh/auth endpoint, and look for:\n\n- 401 on the protected resource \n- 200/204 on the refresh, but no `Set-Cookie` in the response headers, or the cookie is flagged as discarded in the console \n- Subsequent request still lacks the cookie or sends an expired one\n\nIf the cookie is present but the 401 persists, inspect the token payload (jwt.io or the browser’s Application → Cookies view) for missing claims or an `exp` already in the past.\n\nFix the cookie attributes or the refresh logic and the loop disappears.", "error": null, "opened": [], "requested": [], "opened_target": false, "prompt_tokens": 5711, "completion_tokens": 402, "sec": 7.320196866989136, "cost": 0.00814375, "web_tools": [], "n_calls": 1, "nudged": false } ]