Krzysztof kuhy Rudnicki
6258b35f88
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Two independent costs in the background tick, both pure waste.
`list_directory` was called four times per tick -- once by the log pull and
once by each of the three bank syncs. It is the single most expensive call
in a tick at ~445ms mirrored (the GitHub half alone is ~360ms), so that was
~1.3s spent asking the same question four times. It is now listed once in
`run_sync` and passed down.
The curated-bank loop was worse: 17s and 62 requests to fetch *zero* useful
bytes. Firebase returns None for every peer's `food_bank_manual.json`, so
`MirrorSyncClient.get_file_text` treated each miss as "this device has not
migrated yet" and fell through to GitHub, which answers `{}` after ~320ms.
`_primary_only_text` skips that per-peer fallthrough for this one artifact.
Checked before narrowing rather than assumed, because CLAUDE.md requires
both halves of the food bank to sync: reading every peer's curated bank
straight off the mirror found 23 absent, 2 empty, and zero non-empty. No
curated food exists on the mirror alone. The probe is written into the
docstring so it can be re-run before anyone widens this again.
Measured end to end: manual-bank loop 17.0s -> 3.4s, full tick ~27s -> 15.2s,
log/bank/peer state unchanged (441 entries, 117 foods, 22 peers).
`_pull_remote_logs` now returns the revisions it saw instead of mutating a
caller-supplied dict, which keeps it under the argument limit and makes the
data flow visible at the call site.
Deliberately NOT done: revision-skipping the derived food bank. `run_sync`
rebuilds that bank from the merged log immediately before syncing it, so
unlike the log the peer records are not durably held locally -- skipping a
peer would drop its counts from the pushed bank and oscillate under
max-count-wins. Verified empirically: the on-disk bank and a pure log-derived
rebuild are identical (117 foods, 0 differing counts), and the 2 foods peers
know that the local bank lacks are discarded by the existing `if name in
local` filter anyway. The loop is off every interactive path now, so the
remaining cost is background-only.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LJ5YnA3CERitQ57HjMu2Qz
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||
|---|---|---|
| .github/workflows | ||
| app | ||
| diet_guard | ||
| docs | ||
| packaging/aur | ||
| prompts | ||
| scripts | ||
| .gitignore | ||
| .mcp.json | ||
| .pre-commit-config.yaml | ||
| CLAUDE.md | ||
| DESIGN_AUDIT_TODO.md | ||
| diet-guard-gate.service | ||
| diet-guard-gate.timer | ||
| diet-guard-sync.service | ||
| install.sh | ||
| LICENSE | ||
| pyproject.toml | ||
| README.md | ||
| requirements.txt | ||
diet_guard
A log-to-unlock gate: locks the desktop until a meal is logged once a meal slot (08:00 / 12:00 / 16:00 / 20:00) has elapsed without one, and tracks a sealed daily calorie/macro budget.
Install
bash install.sh
This installs the package + dependencies into system Python's user
site-packages (the systemd service runs /usr/bin/python directly, not a
venv — see CLAUDE.md), installs the systemd user timer, seals your daily
budget, and locks the budget file immutable.
Usage
python -m diet_guard init # one-time: compute and seal today's budget
python -m diet_guard gate --demo # test the lock window (safe, closeable)
python -m diet_guard averages # weekly/monthly average kcal vs budget
Averages
averages prints the mean kcal/day for this week, last week, this month and
last month, each labelled under / slightly over / very over.
Three rules make the number honest, and all three are mirrored in the phone app and the gate's History tab:
- the mean is over logged days only -- a day you forgot to log is not a zero-calorie day, and averaging it in as one would make every gap in the log read as "well under budget";
- the yardstick is the mean of the budgets that applied on those same days,
not today's budget, so editing the budget never retroactively reclassifies a
past week (same reason the calendar uses
.budget_history); - today is excluded -- every period ends at yesterday, because a half-logged today drags the mean far enough to flip the band. On a Monday "this week" therefore reports no logged days yet rather than a flattering number.
The band boundaries are the calendar's own (at or under budget / up to 20% over / more than 20% over), so a period and its day cells can never disagree about what "over" means.
The timer runs the gate automatically every ~30 minutes; no manual invocation is needed once installed.
MCP server
An optional Model Context Protocol server
lets an MCP client (Claude Code and its subagents) query today's intake and log
meals as typed tools instead of shelling out to the CLI. It runs in its own
venv (~/.venvs/diet-guard-mcp) so the mcp SDK never touches the
dependency-light system/CLI python path.
Tools:
get_status— today's consumed kcal + macros, the consumption band (on track/approaching limit/OVER BUDGET, or none when no budget is sealed), plus due / logged / current meal slots.list_today— today's logged meals (description, kcal, macros, source, slot).get_slots— the day's fixed meal slots and the current one.get_averages— average kcal/day for this/last week and this/last month, each with its band (under/slightly_over/very_over). Returns the intake and the band only — never the period's average budget.log_meal(description, grams=, kcal=, protein=, carbs=, fat=, slot=, confirm=False)— gated write: withconfirm=Falseit previews the resolved nutrition and target slot and mutates nothing; onlyconfirm=Trueappends the entry. The gate is intrinsic — never add this tool to a permission allowlist, since a client's auto-approve mode would otherwise bypass the human confirmation.
The read tools deliberately never expose the raw daily budget number (only the
qualitative band), nor the sealed .budget file, the shared HMAC key, or the
sync token — the budget stays hidden by design.
Setup:
bash scripts/setup_mcp.sh # create the venv and install diet_guard[mcp]
Then restart Claude Code in this repo and approve the project MCP server
(registered in .mcp.json).
Development
python -m venv .venv && .venv/bin/pip install -r requirements.txt
.venv/bin/pre-commit install && .venv/bin/pre-commit install --hook-type pre-push
.venv/bin/python -m pytest diet_guard/tests/ --cov=diet_guard --cov-branch --cov-fail-under=100
See CLAUDE.md for scheduling details and production deployment gotchas,
and docs/design.md for the original feature spec.