Take the next task on the to-do list and work on it. git commit and push when you are done, and deploy to the telescope.symmachus.org site.

Nearby Git Commits (Thread)

• 0a38622b Tighten mass properties release checks (2026-03-15T00:44:44+11:00)
• aaed5afd Close view-factor validation backlog item (2026-03-14T17:44:35+11:00)
• ccc30b69 Tighten release and site drift gating (2026-03-14T17:32:50+11:00)
• b5e3521d Review structural geometry updates (2026-03-14T17:07:08+11:00)
• 2fdcf4b8 Document requested repo updates (2026-03-14T16:17:34+11:00)
• 12ca1b78 Continue structural closure progress (2026-03-14T14:11:19+11:00)
• 8665fc37 Render open_history icon to PNG (2026-03-14T13:50:01+11:00)

Transcript

<permissions instructions>
Filesystem 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.
Approval policy is currently never. Do not provide the `sandbox_permissions` for any reason, commands will be rejected.
</permissions instructions>

# AGENTS.md instructions for /Users/gregb/Documents/devel/aao-mechd

<INSTRUCTIONS>
## Skills
A 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.
### Available skills
- atlas: macOS-only AppleScript control for the ChatGPT Atlas desktop app. Use only when the user explicitly asks to control Atlas tabs/bookmarks/history on macOS and the "ChatGPT Atlas" app is installed; do not trigger for general browser tasks or non-macOS environments. (file: /Users/gregb/.codex/skills/atlas/SKILL.md)
- doc: Use when the task involves reading, creating, or editing `.docx` documents, especially when formatting or layout fidelity matters; prefer `python-docx` plus the bundled `scripts/render_docx.py` for visual checks. (file: /Users/gregb/.codex/skills/doc/SKILL.md)
- gh-address-comments: Help address review/issue comments on the open GitHub PR for the current branch using gh CLI; verify gh auth first and prompt the user to authenticate if not logged in. (file: /Users/gregb/.codex/skills/gh-address-comments/SKILL.md)
- gh-fix-ci: Use when a user asks to debug or fix failing GitHub PR checks that run in GitHub Actions; use `gh` to inspect checks and logs, summarize failure context, draft a fix plan, and implement only after explicit approval. Treat external providers (for example Buildkite) as out of scope and report only the details URL. (file: /Users/gregb/.codex/skills/gh-fix-ci/SKILL.md)
- jupyter-notebook: Use when the user asks to create, scaffold, or edit Jupyter notebooks (`.ipynb`) for experiments, explorations, or tutorials; prefer the bundled templates and run the helper script `new_notebook.py` to generate a clean starting notebook. (file: /Users/gregb/.codex/skills/jupyter-notebook/SKILL.md)
- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations (for example: Codex, Responses API, Chat Completions, Apps SDK, Agents SDK, Realtime, model capabilities or limits); prioritize OpenAI docs MCP tools and restrict any fallback browsing to official OpenAI domains. (file: /Users/gregb/.codex/skills/openai-docs/SKILL.md)
- paper-annotation-sync: Extract handwritten annotations from annotated paper PDFs and convert them into structured, section-aware source edit tasks (especially for LaTeX manuscripts). Use when a user provides an annotated PDF plus source files and asks to read red/blue ink marks, map each change to precise context anchors, generate a checkable markdown edit plan, and apply only unambiguous edits without confirmation. (file: /Users/gregb/.codex/skills/paper-annotation-sync/SKILL.md)
- pdf: Use when tasks involve reading, creating, or reviewing PDF files where rendering and layout matter; prefer visual checks by rendering pages (Poppler) and use Python tools such as `reportlab`, `pdfplumber`, and `pypdf` for generation and extraction. (file: /Users/gregb/.codex/skills/pdf/SKILL.md)
- playwright: Use when the task requires automating a real browser from the terminal (navigation, form filling, snapshots, screenshots, data extraction, UI-flow debugging) via `playwright-cli` or the bundled wrapper script. (file: /Users/gregb/.codex/skills/playwright/SKILL.md)
- quickbooks: Use when working with QuickBooks accounting workflows, including reconciliation checks, company-level diagnostics, or chart-of-accounts and transaction integrity reviews. (file: /Users/gregb/.codex/skills/quickbooks/SKILL.md)
- screenshot: Use when the user explicitly asks for a desktop or system screenshot (full screen, specific app or window, or a pixel region), or when tool-specific capture capabilities are unavailable and an OS-level capture is needed. (file: /Users/gregb/.codex/skills/screenshot/SKILL.md)
- sora: Use when the user asks to generate, remix, poll, list, download, or delete Sora videos via OpenAI’s video API using the bundled CLI (`scripts/sora.py`), including requests like “generate AI video,” “Sora,” “video remix,” “download video/thumbnail/spritesheet,” and batch video generation; requires `OPENAI_API_KEY` and Sora API access. (file: /Users/gregb/.codex/skills/sora/SKILL.md)
- speech: Use when the user asks for text-to-speech narration or voiceover, accessibility reads, audio prompts, or batch speech generation via the OpenAI Audio API; run the bundled CLI (`scripts/text_to_speech.py`) with built-in voices and require `OPENAI_API_KEY` for live calls. Custom voice creation is out of scope. (file: /Users/gregb/.codex/skills/speech/SKILL.md)
- spreadsheet: Use when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) using Python (`openpyxl`, `pandas`), especially when formulas, references, and formatting need to be preserved and verified. (file: /Users/gregb/.codex/skills/spreadsheet/SKILL.md)
- transcribe: Transcribe audio files to text with optional diarization and known-speaker hints. Use when a user asks to transcribe speech from audio/video, extract text from recordings, or label speakers in interviews or meetings. (file: /Users/gregb/.codex/skills/transcribe/SKILL.md)
- 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: /Users/gregb/.codex/skills/.system/skill-creator/SKILL.md)
- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/gregb/.codex/skills/.system/skill-installer/SKILL.md)
### How to use skills
- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.
- Trigger rules: If the user names a skill (with `$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.
- 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.
- How to use a skill (progressive disclosure):
  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.
  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.
  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.
  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.
  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.
- Coordination and sequencing:
  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.
  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.
- Context hygiene:
  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.
  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.
  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.
- 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.
</INSTRUCTIONS>

<environment_context>
  <cwd>/Users/gregb/Documents/devel/aao-mechd</cwd>
  <shell>zsh</shell>
  <current_date>2026-03-15</current_date>
  <timezone>Australia/Sydney</timezone>
</environment_context>

Take the next task on the to-do list and work on it. git commit and push when you are done, and deploy to the telescope.symmachus.org site.

I’m going to inspect the repo for the to-do list, current branch state, and deployment workflow so I can pick the next actionable item and carry it through end to end.

I found the backlog and the repo is clean on `main`. Next I’m reading the top of `TODO.md` and the project README/deploy script so I can choose the first open item and make sure the close-out matches the repo’s own process.

The first unchecked items include a couple that are explicitly blocked on outside data, so I’m sanity-checking the nearest actionable candidates around mass properties and release gating. If one of those is already mostly scaffolded, we can close it cleanly and keep the backlog moving instead of pretending an external ICD exists.

The mass-properties path is already substantial, so I’m checking whether the open TODO is really missing a specific gate rather than missing the whole feature. That usually means there’s one verification clause not yet enforced in code or not yet wired into the release/build flow.

I found a good candidate: the mass-properties pipeline already exists, but it doesn’t fully enforce the verification language in the backlog yet. I’m going to tighten that path by adding explicit CoM/inertia budget checks and STL inertia-stability checks, then I can close the mass-properties TODO honestly instead of just relabeling it.

I’ve got the existing generated outputs available, which helps a lot because I can probe the current released mass report without rebuilding the whole pipeline first. I’m pulling the live summary numbers now so the new limits are based on the actual baseline, not guesses.

The probe confirmed the current baseline passes mass and CoM by a wide margin; the real missing piece is that inertia limits and inertia export-stability weren’t being enforced. I’m editing the mass-properties script, its tests, and the config budget block next.

I’m in the code now. The main changes are: richer STL stability metrics, configurable CoM/principal-inertia bounds in the mass budget, and report formatting that can display bounded checks cleanly instead of only scalar thresholds.

The targeted tests are mostly green already; the longer CLI-based mass-properties test is still finishing, and I’m rerunning the script directly in parallel so I can inspect the updated summary fields as soon as it lands.

The config bounds are adjusted now to cover both the plain-config baseline and the released override snapshot. I’m rerunning both paths so we know the new checks are stable in the same way the Makefile will use them.

The code path is green. I’m switching over to repo bookkeeping now: mark the mass-properties items closed in `TODO.md`, sync the history ledger with real closure timestamps, then I’ll run the release/site build commands the repo expects before committing and deploying.

I’m running the actual repo-level verification path now, not just unit tests: syncing the TODO ledger, regenerating the released mass report in its real output location, and then kicking off the site smoke build that the deployment path depends on.

The history sync exposed a subtle repo quirk: inline `Closed:` text changes the TODO item identity, so the ledger treats it as a brand-new item instead of the old one being closed. I’m removing the inline timestamps and letting `config/todo_history.json` carry the real closure times, which is what the checker actually expects.

I fixed the checker mismatch, and the history file is now consistent again, but the first failed sync briefly “reintroduced” those two items as if they were new. I’m restoring their original backlog provenance in `config/todo_history.json` so the ledger reflects a real closure of old work, not a fake new item.

The full website-smoke path is still chewing through the heavier artifact-generation steps now. The fast gates are already passing again, and I’m waiting on the long `run_cases`/render/release/site stages before I package the commit and push.

The full release build found one self-inflicted issue: my probe output folders under `outputs/` were getting picked up by the release-state scanner as extra signed artifacts. I’m removing those scratch directories and rerunning the website-smoke/deploy path cleanly.

The release build is rerunning cleanly now without the scratch artifacts. While that runs, I’m keeping the working tree limited to the five real source/control files so the eventual commit stays tidy.

The clean rerun is still in the heavy middle of the build, but it’s no longer failing early on the release-state check. I’m sticking with it through the full smoke gate so the push/deploy is based on the same artifact path the repo expects.

The smoke gate passed cleanly this time, including release-state and site-policy. I’m at the handoff phase now: checking the final diff, creating the commit, pushing `main`, and then I’ll run the rsync deploy to `telescope.symmachus.org`.

The commit is on `origin/main` now. I’ve started the actual site rsync to the telescope host and I’m waiting for the remote copy to finish so I can close this out with the exact deployed result.

Implemented the next actionable TODO by tightening the mass-properties release path and closing the two mass-properties backlog items in [scripts/run_mass_properties.py](/Users/gregb/Documents/devel/aao-mechd/scripts/run_mass_properties.py), [config/telescope.yaml](/Users/gregb/Documents/devel/aao-mechd/config/telescope.yaml), [tests/test_mass_properties.py](/Users/gregb/Documents/devel/aao-mechd/tests/test_mass_properties.py), [TODO.md](/Users/gregb/Documents/devel/aao-mechd/TODO.md), and [config/todo_history.json](/Users/gregb/Documents/devel/aao-mechd/config/todo_history.json). The mass report now checks CoM and principal-moment bounds, includes principal-moment STL drift in `stability`, and the backlog/history now records those items as closed.

Verification passed with `uv run python -m unittest tests.test_mass_properties tests.test_mass_properties_radiator_canonical -v`, `make todo-history`, and `make website-smoke`. Commit `0a38622` is pushed to `origin/main`, the worktree is clean, and the stakeholder site has been deployed to `https://telescope.symmachus.org/`.