ℹ️ About Codex in GitHub

\\n
\\n\\n[Your team has set up Codex to review pull requests in this repo](https://chatgpt.com/codex/cloud/settings/general). Reviews are triggered when you\\n- Open a pull request for review\\n- Mark a draft as ready\\n- Comment \\\"@codex review\\\".\\n\\nIf Codex has suggestions, it will comment; otherwise it will react with 👍.\\n\\n\\n\\n\\nCodex can also answer questions or update the PR. Try commenting \\\"@codex address that feedback\\\".\\n \\n

\",\"path\":null,\"side\":null,\"line\":null}","text_elements",[],{"_373":671,"_360":361,"_375":363},{"_376":672,"_378":-5,"_41":-5,"_379":-5,"_95":284,"_91":381},[673],{"_45":667,"_91":674},"input_text","turn/started",{"_360":361,"_86":677},{"_102":-5,"_41":363,"_364":678,"_366":679},[],"inProgress",{"_366":681,"_360":361},{"_682":683,"_91":684},"activeFlags",[],"active",{"_373":686,"_360":361,"_375":687},{"_376":688,"_378":-5,"_41":-5,"_379":-5,"_95":284,"_91":381},"auto-compact-0",[689,690],{"_45":692,"_91":674},{"_45":691,"_91":674},"\n /workspace/brainflow\n bash\n 2026-04-28\n Etc/UTC\n","# AGENTS.md instructions for /workspace/brainflow\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /opt/codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /opt/codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.\n",{"_373":694,"_360":361,"_375":687},{"_376":695,"_378":-5,"_41":-5,"_379":-5,"_95":696,"_91":381},[697],"developer",{"_45":698,"_91":674},"\nFilesystem sandboxing defines which files can be read or written. `sandbox_mode` is `danger-full-access`: No filesystem sandboxing - all commands are permitted. Network access is enabled.\nApproval policy is currently never. Do not provide the `sandbox_permissions` for any reason, commands will be rejected.\n","thread/started",{"_701":702},"thread",{"_703":-5,"_704":-5,"_705":706,"_707":708,"_417":418,"_709":15,"_710":-5,"_711":-5,"_41":361,"_712":713,"_166":-5,"_156":714,"_715":180,"_423":716,"_366":717,"_76":718,"_719":708},"agentNickname","agentRole","cliVersion","0.114.0","createdAt",1777339917,"ephemeral","forkedFromId","gitInfo","modelProvider","openai","/opt/codex/sessions/2026/04/28/rollout-2026-04-28T01-31-57-019dd1b6-e431-7e32-918c-38147d9b9785.jsonl","preview","vscode",{"_91":370},[],"updatedAt",[],"messages",[723],{"_41":724,"_725":726,"_727":728,"_729":728,"_376":730,"_366":731,"_378":-5,"_732":31,"_733":734,"_735":736,"_737":-5},"9f9bf57e-a7a5-42bb-818b-89ee635e488e","author",{"_95":284,"_166":-5,"_733":746},"create_time",1777339917.044566,"update_time",{"_742":45,"_743":744},"finished_successfully","weight","metadata",{"_738":739},"recipient","all","channel","l1239dk1",{"_740":741},"inline_comments",[],"content_type","parts",[745],"@codex adress this feedback (path=src/board_controller/muse/muse_anthena.cpp line=983 side=RIGHT)\nfix muse s anthena timestamps\n\n\nComments in the same thread:\n\n**_{_{![P1 Badge](https://img.shields.io/badge/P1-orange?style=flat)}} Keep per-packet timestamp interpolation monotonic**\n\nThe new `get_sample_timestamp` logic can emit decreasing timestamps within a single payload because it decides per sample whether to use `last + (sample+1)/sampling_rate` or the interpolated `step` fallback. When `current_timestamp - last_timestamp` is smaller than `n_samples/sampling_rate` but larger than some early sample offsets (a normal jitter case), early samples take the fixed-rate path while later ones switch to interpolation, which can move backwards (e.g., with `n_samples=4`, `sampling_rate=256`, `dt=10ms`: sample 1 is `7.8125ms`, sample 2 becomes `7.5ms`). This breaks monotonic timestamps and can corrupt downstream time-based processing.\n\nUseful? React with 👍 / 👎.\n\n### 💡 Codex Review\n\nHere are some automated review suggestions for this pull request.\n\n**Reviewed commit:** `7f619fd385`\n \n\n

ℹ️ About Codex in GitHub

\n
\n\n[Your team has set up Codex to review pull requests in this repo](https://chatgpt.com/codex/cloud/settings/general). Reviews are triggered when you\n- Open a pull request for review\n- Mark a draft as ready\n- Comment \"@codex review\".\n\nIf Codex has suggestions, it will comment; otherwise it will react with 👍.\n\n\n\n\nCodex can also answer questions or update the PR. Try commenting \"@codex address that feedback\".\n \n

",{},"created",1777339980.0928006,"Completing the task","event_type","info",{"_91":381,"_95":92,"_376":781},{"_91":778,"_779":780},{"_91":755,"_756":466,"_757":758,"_759":760,"_761":-5},"pr","pr_title","pr_message","### Motivation\n- Prevent non-monotonic per-packet sample timestamps in `src/board_controller/muse/muse_anthena.cpp` caused by mixing fixed-rate and fallback interpolation per sample under jitter.\n\n### Description\n- Update `get_sample_timestamp` to pick a single interpolation mode per payload: use fixed sampling-rate spacing when `(current_timestamp - last_timestamp) >= n_samples / sampling_rate`, otherwise interpolate all samples evenly across the packet interval to preserve monotonicity.\n\n### Testing\n- Verified the patch formatting and behavior with `git diff --check -- src/board_controller/muse/muse_anthena.cpp` which passed, and inspected the repository diff with `git status --short && git diff -- src/board_controller/muse/muse_anthena.cpp`.","output_diff",{"_91":759,"_762":418,"_127":128,"_763":-5,"_283":764,"_765":766,"_767":644,"_768":454,"_769":770,"_771":772,"_773":774},"pre_apply_patch","repo_id","preapply_patch_base_commit_sha","diff --git a/src/board_controller/muse/muse_anthena.cpp b/src/board_controller/muse/muse_anthena.cpp\nindex dd1b29e8a7fc52043a869644a258bda089084b4b..f0dcf5d156bb841bd14f42e235caf57f646f2911 100644\n--- a/src/board_controller/muse/muse_anthena.cpp\n+++ b/src/board_controller/muse/muse_anthena.cpp\n@@ -955,48 +955,51 @@ void MuseAnthena::parse_sensor_payload (\n void MuseAnthena::reset_timestamps ()\n {\n last_eeg_timestamp = -1.0;\n last_aux_timestamp = -1.0;\n last_anc_timestamp = -1.0;\n }\n \n double MuseAnthena::get_sample_timestamp (double last_timestamp, double current_timestamp,\n int sample_index, int n_samples, double sampling_rate)\n {\n if ((n_samples <= 0) || (sampling_rate <= 0.0))\n {\n return current_timestamp;\n }\n \n if (last_timestamp <= 0.0)\n {\n return current_timestamp - (double)(n_samples - sample_index - 1) / sampling_rate;\n }\n \n if (current_timestamp <= last_timestamp)\n {\n return current_timestamp;\n }\n \n- double sample_timestamp = last_timestamp + (double)(sample_index + 1) / sampling_rate;\n- if (sample_timestamp <= current_timestamp)\n+ // Choose a single interpolation mode per payload to keep timestamps monotonic.\n+ // If we have enough wall-clock span for fixed-rate samples, use sampling-rate spacing.\n+ // Otherwise, distribute samples evenly between packet boundaries.\n+ const double packet_duration = (double)n_samples / sampling_rate;\n+ if ((current_timestamp - last_timestamp) >= packet_duration)\n {\n- return sample_timestamp;\n+ return last_timestamp + (double)(sample_index + 1) / sampling_rate;\n }\n \n- double step = (current_timestamp - last_timestamp) / (double)n_samples;\n+ const double step = (current_timestamp - last_timestamp) / (double)n_samples;\n return last_timestamp + step * (double)(sample_index + 1);\n }\n \n std::string MuseAnthena::bytes_to_string (const uint8_t *data, size_t size)\n {\n std::ostringstream oss;\n for (size_t i = 0; i < size; i++)\n {\n if (i > 0)\n {\n oss << \" \";\n }\n oss << static_cast (data[i]);\n }\n return oss.str ();\n }\n","external_storage_diff",{"_775":776,"_777":-5},"files_modified","lines_added","lines_removed",4,"commit_message","Fix Muse Anthena per-packet timestamp monotonicity","additional_parent_commit_shas",[],"file_id","file_00000000333871f5b8be7415707a37a5","ttl","partial_repo_snapshot","files",[],[782],{"_742":45,"_45":383},{"_91":284,"_41":83,"_95":284,"_785":786,"_787":788,"_789":790,"_131":-5,"_118":791},[82],"input_items",[807,808,809,810],"external_post_config",{"_792":793,"_224":225,"_794":265,"_236":-5,"_762":219,"_795":-5,"_796":797,"_798":755,"_799":-5,"_800":-5,"_801":802,"_803":15,"_804":57,"_805":52,"_806":15},"user_model_slug","slug",1777339812.258765,"installation_id",113056376,"pr_number","review_trigger","comment_id",3148733781,"comment_type","pr_write_guard_token","pending_pr_reaction_id","pending_comment_reaction_id",385394894,"comment_if_no_findings","comment_on_error","share_url","is_parallel_review",{"_91":381,"_95":284,"_376":821},{"_272":273,"_274":180,"_818":278,"_819":128,"_280":-5,"_91":820},{"_91":811,"_274":815,"_156":429,"_813":816,"_814":817},{"_91":811,"_274":812,"_156":-5,"_813":-5,"_814":-5},"pull_request_comment","\n### 💡 Codex Review\n\nHere are some automated review suggestions for this pull request.\n\n**Reviewed commit:** `7f619fd385`\n \n\n

ℹ️ About Codex in GitHub

","side","line","Comments in the same thread:\n\n**_{_{![P1 Badge](https://img.shields.io/badge/P1-orange?style=flat)}} Keep per-packet timestamp interpolation monotonic**\n\nThe new `get_sample_timestamp` logic can emit decreasing timestamps within a single payload because it decides per sample whether to use `last + (sample+1)/sampling_rate` or the interpolated `step` fallback. When `current_timestamp - last_timestamp` is smaller than `n_samples/sampling_rate` but larger than some early sample offsets (a normal jitter case), early samples take the fixed-rate path while later ones switch to interpolation, which can move backwards (e.g., with `n_samples=4`, `sampling_rate=256`, `dt=10ms`: sample 1 is `7.8125ms`, sample 2 becomes `7.5ms`). This breaks monotonic timestamps and can corrupt downstream time-based processing.\n\nUseful? 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