Climate Zone Mapper

Every energy code asks the same question of a building envelope: what is required at each component, for this site's zone. The component list is the same everywhere. The zone names and the numbers are not, so both come from you.

Workflow

Step 1. Bootstrap if needed

python scripts/init_workspace.py

Confirm before creating docs/ in a project that does not have one.

Step 2. Establish the code and the zone

Ask, in one message:

1. Which energy code governs, and which edition? Name any local amendment layered on top, and say which governs where they differ.
2. What zone is the site in, and where did that come from? A county listing in the code, a map, a climate data standard, or a letter from the authority. Name it; the source prints on the scorecard.
3. Is this scored as commercial or residential, in your code's sense of those words?
4. How will you supply the requirements? Type them, paste the table row, or name a file I should read.

If the zone is unknown, stop. Everything downstream is keyed to it, and a scorecard built on a guessed zone is wrong in a way that looks entirely normal.

Step 3. Collect the proposed assemblies

For each component, ask what is proposed and in what units. Never fill one in from a typical construction.

Step 4. Collect one requirement per component

Work the list below. For each, accept a typed value with its clause, a pasted table row to read it out of, or a file to read. If none arrives, the component is unverified.

#	Component	Usually expressed as
1	Roof	thermal resistance, or assembly transmittance
2	Walls above grade	thermal resistance, or assembly transmittance
3	Walls below grade	thermal resistance, and the depth it applies to
4	Floors over unconditioned space	thermal resistance
5	Slab on grade edge	thermal resistance, and the depth or width
6	Fenestration, thermal	assembly transmittance
7	Fenestration, solar	solar heat gain coefficient
8	Air leakage	rate, and the pressure it is tested at

State which row you took, since these tables are keyed by zone and by commercial against residential, and a right number off the wrong row reads exactly like a right answer.

Step 5. Score

#	Component	Required	Cited as	Row taken	Proposed	Status

Status is pass, fail, unverified (no requirement supplied), missing (no assembly supplied), or n/a.

Write the CSV to docs/climate-zone/<project>-envelope.csv and the summary from assets/climate-zone-summary-template.md. Both carry the code, the edition, the zone, and the zone's source at the head, and the unverified count at the foot.

Step 6. Update the index

python scripts/append_to_index.py \
  --project <slug> \
  --location "<as supplied>" \
  --county-state "<as supplied>" \
  --zone "<as supplied>" \
  --occupancy "<Commercial | Residential>" \
  --csv <file>.csv \
  --summary <file>.md

Do not edit docs/climate-zone/index.md by hand; the table alignment breaks.

Step 7. Report

Counts by status, the unverified list with what each needs, and:

The zone and every requirement here came from you. I compared numbers and supplied none. Unverified components were not scored at all.

Rules

• Never supply a zone or a requirement. Not from memory, not from a search, not from a figure in this file. There are none in this file.
• Record where the zone came from, on the scorecard, every time. A zone without a source cannot be defended a year later.
• Name the row every requirement came from, including the commercial or residential split.
• Never convert units and never round a requirement or a proposed value.
• Stop if the zone is unknown. Do not score against a guess.
• Where a base code and a local amendment both apply, the user says which governs each row; never merge them.

Anti-patterns

• Naming the zone for a city because the answer feels obvious. Zone boundaries are drawn at county lines and get redrawn between editions.
• Filling a thermal resistance or a transmittance from recall because the combination is a common one.
• Searching the web for a table row and scoring against what comes back.
• Reporting only the components that could be scored.
• Scoring a residential assembly against a commercial row, or the reverse.
• Editing docs/climate-zone/index.md directly instead of using the script.
• Bundling a zone list or an envelope table into this skill later. It had both. An audit found the original tables had been generated from model recall rather than read from the publication, and every cell was replaced with a verification placeholder; the tables and the script that parsed them were removed rather than filled back in.

Resources

• assets/climate-zone-summary-template.md — the summary structure.
• assets/climate-zone-index-template.md — the project index structure.
• scripts/init_workspace.py — bootstrap docs/climate-zone/.
• scripts/append_to_index.py — append a row to the index.

No reference files. The zone and the requirements come from your code.