Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add chemrich/cabineteer --skill add-presetgit clone --depth 1 https://github.com/chemrich/cabineteerWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/chemrich/cabineteer/add-preset)<a href="https://agentmods.dev/skills/chemrich/cabineteer/add-preset"><img src="https://agentmods.dev/badge/skills/chemrich/cabineteer/add-preset/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/chemrich/cabineteer/add-preset"><img src="https://agentmods.dev/badge/skills/chemrich/cabineteer/add-preset.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00068 | $0.00950 |
| Opus 5 | $0.00034 | $0.00475 |
| Sonnet 5 | $0.00014 | $0.00190 |
| Haiku 4.5 | $0.00007 | $0.00095 |
Grade A, and why
add-preset scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adding a cabinet preset
Presets live in src/cabineteer/presets.py as frozen CabinetPreset dataclasses, registered by wrapping each in _p(...).
Steps
-
Add the preset near the others in its category section:
_p(CabinetPreset( name="workshop_tool_chest", # slug for apply_preset (kebab/snake, unique) display_name="Workshop Tool Chest", # human label description="One-line use-case description.", category="workshop", # kitchen | workshop | bedroom | bathroom | storage tags=["workshop", "drawer", "tool"], # searchable difficulty="standard", # basic | standard | advanced config=CabinetConfig( width=900, height=720, depth=550, openings=[ # (height_mm, opening_type) bottom→top (300, "drawer"), (192, "drawer"), (192, "drawer"), ], drawer_slide="blum_tandem_550h", door_hinge="blum_clip_top_110_full", carcass_joinery=CarcassJoinery.DADO_RABBET, ), )) -
Honor the opening-stack invariant. The opening heights must sum to the interior height =
height - top_thickness - bottom_thickness(default720 - 18 - 18 = 684). A stack that over-fills raises an ERROR (the guard test rejects it). A stack that sums exactly to interior — which every existing preset does — raises a benigncumulative_heightsWARNING (zero reveal at the top); that is accepted, not something to design away. The bar for a preset is zero ERROR-severity issues, warnings allowed. -
Use real hardware keys.
drawer_slide/door_hinge/drawer_pull/door_pullmust exist inhardware.py(SLIDES,HINGES,PULLS). An unknown key is not silently dropped or resolved toNone— it raisesKeyError(loudly, listing the available keys) as soon as the hardware is consulted for a matching opening, e.g. when youevaluate_cabinetor generate a cutlist for a config that has the relevant drawer/door. Check valid keys withlist_hardwareor by grepping the spec dicts.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 56 lines · 68 tokens per session scan A 34a25fd6b260
add-preset is a skill published in the GitHub repository chemrich/cabineteer (3 stars, last pushed 6d ago), licensed Apache-2.0. It adds 68 tokens to every session and 950 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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