Agent skill

Adu Plan Review

by mikeOnBreeze in mikeOnBreeze/cc-crossbeam

City-side ADU plan review — the flip side of adu-corrections-flow.

MITAuto-check passedDocuments & Office

Install Adu Plan Review

skills CLI
$ npx skills add mikeOnBreeze/cc-crossbeam --skill adu-plan-review -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mikeOnBreeze/cc-crossbeam adu-plan-review --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mikeOnBreeze/cc-crossbeam.git skills-src && mkdir -p .claude/skills && cp -r skills-src/server/skills/adu-plan-review .claude/skills/adu-plan-review && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
adu-plan-review
GitHub stars
293
Token cost
~3.7k tokens
SKILL.md length
1,641 words
Files
2 (incl. references)
Skills in repo
20
Repo updated
First seen
Licence
MIT

At a glance

City-side ADU plan review — the flip side of adu-corrections-flow.

  • Works in 4 steps: Extract & Map → Sheet-by-Sheet Review (FILE-BASED) → Code Compliance (FILE-BASED, concurrent… → …
  • A city plan checker uploads a plan binder for AI-assisted review
  • SKILL.md covers Overview, Sub-Skills, City Routing and Inputs, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Adu Plan Review is an agent skill from mikeOnBreeze/cc-crossbeam. City-side ADU plan review — the flip side of adu-corrections-flow. Takes a plan binder PDF + city name, reviews each sheet against code-grounded checklists, checks state and city compliance, and generates a draft corrections letter with confidence flags and reviewer blanks. Coordinates three sub-skills (california-adu for state law, adu-city-research OR a dedicated city skill for city rules, adu-targeted-page-viewer for plan extraction). Triggers when a city plan checker uploads a plan binder for AI-assisted…

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/checklist-cover.md`).

It sits in Documents & Office, covering PDF. The repository describes itself as: CrossBeam Permits — AI-assisted building-permit plan review for cities and builders. The licence is MIT.

When your agent uses it

  • A city plan checker uploads a plan binder for AI-assisted review
  • Tasks that involve PDF

Example prompts

  • “/adu-plan-review”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Extract & Map
  2. Sheet-by-Sheet Review (FILE-BASED)
  3. Code Compliance (FILE-BASED, concurrent 3A + 3B)
  4. Merge & Draft Corrections (FILE-BASED, dedicated subagent)

What it can do on your machine

Read from SKILL.md and the folder at commit cc5591e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Adu Plan Review loads about 3.7k tokens when it runs, and up to ~9.7k if it reads all its reference files. Until then it costs about 134 tokens; SKILL.md has 1,641 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~134
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~9.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from mikeOnBreeze/cc-crossbeam at commit cc5591e, republished under its MIT licence (© mikeOnBreeze). 1,641 words, ~3,709 tokens.

Download SKILL.mdSave it as .claude/skills/adu-plan-review/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
adu-plan-review
description
City-side ADU plan review — the flip side of adu-corrections-flow. Takes a plan binder PDF + city name, reviews each sheet against code-grounded checklists, checks state and city compliance, and generates a draft corrections letter with confidence flags and reviewer blanks. Coordinates three sub-skills (california-adu for state law, adu-city-research OR a dedicated city skill for city rules, adu-targeted-page-viewer for plan extraction). Triggers when a city plan checker uploads a plan binder for AI-assisted review.

ADU Plan Review — City Corrections Generator

Overview

Review ADU construction plan submittals and generate a draft corrections letter. This is the city-side counterpart to the contractor-side adu-corrections-flow.

SkillDirectionInputOutput
adu-corrections-flowContractor → interprets correctionsCorrections letter + plansContractor questions + response package
adu-plan-review (this skill)City → generates correctionsPlan binder + city nameDraft corrections letter

Same domain knowledge, opposite direction.

Sub-Skills

SkillRoleWhen
adu-targeted-page-viewerExtract PDF → PNGs + sheet manifestPhase 1
california-aduState-level code compliance (28 reference files, offline)Phase 3A
City-specific skill OR adu-city-researchCity rules — see City Routing belowPhase 3B

City Routing

The city knowledge source depends on whether the city has been onboarded:

Input: city_name

IF dedicated city skill exists (e.g., placentia-adu/):
  → Tier 3: Load city skill reference files (offline, fast, ~30 sec)
ELSE:
  → Tier 2: Run adu-city-research
    → Mode 1 (Discovery): WebSearch for city URLs (~30 sec)
    → Mode 2 (Extraction): WebFetch discovered URLs (~60-90 sec)
    → Mode 3 (Browser Fallback): Only if extraction has gaps (~2-3 min)

How to detect onboarded cities: Check for a city skill directory at skill/{city-slug}-adu/SKILL.md. If it exists, the city is onboarded. If not, fall back to web research.

Tier 1 (state law only) is always available — it's the california-adu skill. Even without any city knowledge, state law catches ~70% of common corrections.

Inputs

InputFormatRequired
Plan binderPDF (full construction plan set)Yes
City nameStringYes
Project addressStringRecommended (improves city research)
Review scopefull or administrativeOptional — defaults to full

Review scope options:

  • administrative — Cover sheet, sheet index, stamps/signatures, governing codes, project data. Fast (~2 min), HIGH confidence. Good for completeness screening.
  • full — All sheet types, all check categories. Slower (~5-8 min), mixed confidence. Produces the draft corrections letter.

Outputs

All written to the session directory.

OutputFormatPhase
sheet-manifest.jsonSheet ID ↔ page mappingPhase 1 (pre-loaded)
findings-arch-a.jsonArchitectural A findings (cover + floor plans)Phase 2
findings-arch-b.jsonArchitectural B findings (elevations + sections)Phase 2
findings-site-civil.jsonSite/Civil findings (site plan + energy/code)Phase 2
findings-structural.jsonStructural findings (foundation + framing + details)Phase 2
findings-mep-energy.jsonMEP/Energy findings (plumbing + mechanical + electrical + T24)Phase 2
state_compliance.jsonState law findings relevant to plan issuesPhase 3A
city_compliance.jsonCity-specific findings (from city skill or web research)Phase 3B
draft_corrections.jsonDraft corrections letter — the main outputPhase 4
draft_corrections.mdFormatted markdown corrections letterPhase 4
review_summary.jsonStats: items found by confidence tier, review coverage, reviewer action itemsPhase 4

Workflow

Phase 1: Extract & Map

Run adu-targeted-page-viewer:

  1. Check first: PNGs and title block crops may already be pre-extracted in project-files/pages-png/ and project-files/title-blocks/. If they exist, skip extraction and go straight to reading the cover sheet.
  2. If PNGs don't exist: Extract PDF pages to PNGs: scripts/extract-pages.sh <binder.pdf> <output-dir>
  3. Read cover sheet for sheet index
  4. Match sheet IDs to pages (title block reading if needed)
  5. Save sheet-manifest.json

~90 seconds (or ~30 seconds if PNGs are pre-extracted). Identical to Phase 2 of adu-corrections-flow.

Phase 2: Sheet-by-Sheet Review (FILE-BASED)

Review each sheet against the relevant checklist reference file. Group sheets by discipline to limit subagent count. Subagents write findings to files — they do NOT return findings to the orchestrator.

Subagent grouping:

SubagentSheetsChecklist ReferenceOutput File
arch-aCover sheet, floor plan(s)checklist-cover.md, checklist-floor-plan.mdoutput/findings-arch-a.json
arch-bElevations, roof plan, building sectionschecklist-elevations.mdoutput/findings-arch-b.json
site-civilSite plan, grading plan, utility planchecklist-site-plan.mdoutput/findings-site-civil.json
structuralFoundation, framing, structural detailschecklist-structural.mdoutput/findings-structural.json
mep-energyPlumbing, mechanical, electrical, Title 24checklist-mep-energy.mdoutput/findings-mep-energy.json

Rolling window: 3 subagents in flight. arch-a + arch-b + site-civil start first. As each completes, launch the next.

Each subagent receives:

  • The sheet PNG(s) for its assigned sheets (read from pages-png/)
  • The relevant checklist reference file(s)
  • The sheet manifest (for cross-reference context)
  • Instructions to WRITE findings to its output file

Each subagent WRITES a findings JSON file containing an array — one entry per check:

  • check_id — Which checklist item (e.g., "1A" = architect stamp)
  • sheet_id — Which sheet (e.g., "A1")
  • status — PASS | FAIL | UNCLEAR | NOT_APPLICABLE
  • visual_confidence — HIGH | MEDIUM | LOW
  • observation — What the subagent actually saw (evidence)
  • code_ref — Code section this check is grounded in

Each subagent RETURNS only a short summary (e.g., "Done, wrote 12 findings to findings-arch-a.json"). The orchestrator collects this summary via TaskOutput but does NOT read the findings file.

Orchestrator verification: After all 5 subagents complete, use Glob to verify all 5 findings-*.json files exist. Do NOT read their contents.

~2-3 minutes for full review (5 subagents, 3-at-a-time rolling window).

Phase 3: Code Compliance (FILE-BASED, concurrent 3A + 3B)

After Phase 2 completes, launch two concurrent subagents to verify findings against code. Both subagents read findings from disk and write results to disk.

3A: State Law Verification
  • Skill: california-adu
  • Input: Read all findings-*.json files from the output directory. Focus on FAIL and UNCLEAR findings.
  • Task: For each finding, look up the cited code section in the california-adu reference files. Verify: Is this actually required by state law? What are the exact thresholds? Are there ADU-specific exceptions?
  • Output: Write output/state_compliance.json — per-finding code verification with exact citations
  • Return: Short summary only (e.g., "Done, verified 18 findings against state law, wrote state_compliance.json")

Why this matters: The checklist reference files cite code sections, but the california-adu skill has the detailed rules with exceptions and thresholds. Phase 3A catches false positives — e.g., the checklist flags a 3-foot setback, but the ADU is a conversion and conversions have no setback requirement.

3B: City Rules

Route based on City Routing decision (see above).

If onboarded city (Tier 3):

  • Read all findings-*.json files from the output directory
  • Load city skill reference files
  • Check findings against city-specific amendments, standard details, and IBs
  • Fast — ~30 sec, all offline

If web research (Tier 2):

  • Read all findings-*.json files from the output directory
  • Run adu-city-research Mode 1 → Mode 2 → optional Mode 3
  • Check findings against discovered city requirements
  • Slower — ~90 sec to 3 min

Output: Write output/city_compliance.json — city-specific requirements, local amendments, standard details that apply to the findings Return: Short summary only

Orchestrator verification: After both subagents complete, use Glob to verify state_compliance.json and city_compliance.json exist. Do NOT read their contents.

Show full SKILL.md (705 more words)Show less
Phase 4: Merge & Draft Corrections (FILE-BASED, dedicated subagent)

This is a dedicated subagent — the orchestrator does NOT merge findings itself. The Phase 4 subagent reads all artifact files from disk and produces the corrections letter.

Subagent reads from disk:

  1. output/findings-*.json (5 files from Phase 2) — what the AI found on the plans
  2. output/state_compliance.json (Phase 3A) — state law verification
  3. output/city_compliance.json (Phase 3B) — city-specific rules
  4. output/sheet-manifest.json (Phase 1) — for sheet references

For each finding, apply this filter:

ConditionAction
Finding confirmed by state AND/OR city codeInclude in corrections letter with code citation
Finding confirmed by code but visual confidence is LOWInclude with [VERIFY] flag
Finding not confirmed by any code (no legal basis)DROP IT — do not include
Finding relates to engineering/structural adequacyInclude as [REVIEWER: ...] blank
Finding requires subjective judgmentDROP IT — prohibited for ADUs per Gov. Code § 66314(b)(1)

Output format — draft_corrections.json:

Each correction item includes:

  • item_number — Sequential
  • section — Building, Fire/Life Safety, Site/Civil, Planning/Zoning
  • description — The correction text (what needs to be fixed)
  • code_citation — Specific code section(s)
  • sheet_reference — Which sheet(s) are affected
  • confidence — HIGH | MEDIUM | LOW
  • visual_confidence — How certain the AI is about the visual observation
  • reviewer_action — CONFIRM (quick check) | VERIFY (needs closer look) | COMPLETE (reviewer must fill in)

See references/output-schemas.md for full JSON schema.

Subagent writes 3 files:

  • output/draft_corrections.json — structured corrections data
  • output/draft_corrections.md — formatted markdown corrections letter (primary output for frontend + PDF conversion)
  • output/review_summary.json — stats: items by confidence tier, review coverage, reviewer action items

Return: Short summary only (e.g., "Done, generated 14 corrections, wrote draft_corrections.json/md + review_summary.json")

PDF generation is handled externally — after this agent completes, the server converts draft_corrections.md to PDF outside the sandbox. Do NOT attempt PDF generation. Do NOT use adu-corrections-pdf. Do NOT install reportlab, puppeteer, or any PDF tools. Your job ends at draft_corrections.md.

Orchestrator verification: After Phase 4 subagent completes, verify draft_corrections.json, draft_corrections.md, and review_summary.json exist. Do NOT read their contents.

Timing

PhaseTimeNotes
Phase 1~90 secPDF extraction + manifest
Phase 2~2-3 min5 subagents, 3-at-a-time rolling window
Phase 3A~60 secState law lookup (offline)
Phase 3B (Tier 3)~30 secOnboarded city — offline
Phase 3B (Tier 2)~90 sec–3 minWeb research — depends on city
Phase 4~2 minMerge + filter + format markdown
Total (Tier 3 city)~5-7 min
Total (Tier 2 city)~7-10 min
Administrative scope only~3-4 minCover sheet checks only

Reference Files

Checklist References (what to check per sheet type)
FileSheet TypeStatus
references/checklist-cover.mdCover / title sheetDraft
references/checklist-site-plan.mdSite plan, grading, utilitiesTODO
references/checklist-floor-plan.mdFloor plan(s)TODO
references/checklist-elevations.mdElevations, roof plan, sectionsTODO
references/checklist-structural.mdFoundation, framing, detailsTODO
references/checklist-mep-energy.mdPlumbing, mechanical, electrical, Title 24TODO
Output References
FileContentsStatus
references/output-schemas.mdJSON schemas for all output filesTODO
references/corrections-letter-template.mdHow to format the draft corrections letterTODO
Sub-Skill References
SkillRoleReference
california-aduState law (Phase 3A)california-adu/AGENTS.md — 28 reference files
adu-city-researchCity rules via web (Phase 3B Tier 2)Modes 1/2/3 in its SKILL.md
adu-targeted-page-viewerPlan extraction (Phase 1)Sheet manifest workflow in its SKILL.md

Important Notes

  • No false positives. A city tool that generates incorrect corrections destroys trust. Phase 4's filter is designed to DROP findings that lack code basis rather than include them with low confidence. Err on the side of missing something (the human reviewer catches it) rather than flagging something incorrectly.
  • Reviewer blanks > AI guesses. For structural, engineering, and judgment-call items, insert [REVIEWER: describe what needs human assessment] rather than attempting an assessment. The AI's job is the repeatable 60%, not the expert 40%.
  • Objective standards only. Per Gov. Code § 66314(b)(1), ADUs can only be subject to objective (measurable, verifiable) standards. If a potential finding requires subjective judgment ("design doesn't match neighborhood character"), do NOT include it. This is the law.
  • State preemption. State law sets minimum ADU rights. If city rules are MORE restrictive than state law, flag the conflict — the state law prevails. The california-adu skill is the authority on state requirements.
  • Two confidence dimensions. Every finding has both code confidence (is this legally required?) and visual confidence (am I right about what I see?). Both must be reported. A reviewer needs to know "the law is clear but I'm not sure what I see" vs. "I can clearly see this but I'm not sure it's required."

© mikeOnBreeze, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in server/skills/adu-plan-review of mikeOnBreeze/cc-crossbeam.

  • SKILL.md
  • references/checklist-cover.md

Open the folder on GitHubat commit cc5591e

Compare with similar skills

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Questions about Adu Plan Review

What does Adu Plan Review do?

City-side ADU plan review — the flip side of adu-corrections-flow. Adu Plan Review is an agent skill from mikeOnBreeze/cc-crossbeam. City-side ADU plan review — the flip side of adu-corrections-flow.

When should I use Adu Plan Review?

Adu Plan Review fits situations like: A city plan checker uploads a plan binder for AI-assisted review; tasks that involve PDF.

How do I install Adu Plan Review in Claude Code?

Run `npx skills add mikeOnBreeze/cc-crossbeam --skill adu-plan-review -a claude-code`. Or copy the skill folder (server/skills/adu-plan-review in mikeOnBreeze/cc-crossbeam) into .claude/skills/adu-plan-review in your project. Claude Code loads it when a task matches its description.

How do I install Adu Plan Review in Codex?

Run `npx skills add mikeOnBreeze/cc-crossbeam --skill adu-plan-review -a codex`. Or copy the skill folder (server/skills/adu-plan-review in mikeOnBreeze/cc-crossbeam) into .agents/skills/adu-plan-review in your project. Codex loads it when a task matches its description.

Can I use Adu Plan Review in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mikeOnBreeze/cc-crossbeam --skill adu-plan-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/adu-plan-review, .gemini/skills/adu-plan-review, .github/skills/adu-plan-review and .opencode/skills/adu-plan-review in your project.

What does Adu Plan Review need to run?

SKILL.md names no scripts, command-line tools or credentials: Adu Plan Review is instructions for the agent only.

Does Adu Plan Review access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Adu Plan Review safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Adu Plan Review use?

Adu Plan Review is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Adu Plan Review use?

About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 6k tokens, read only when the agent opens those files.

What are the alternatives to Adu Plan Review?

Skills that share tags, products or a category with Adu Plan Review: Markitdown (ImCa0/just-laws, 781 stars), Gzh Design (isjiamu/gzh-design-skill, 4k stars), GenOffice Document CLI (genspark-ai/genoffice, 9.2k stars) and Harness Book Best Practice (wquguru/harness-books, 3.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Adu Plan Review?

mikeOnBreeze (a GitHub user) maintains it in mikeOnBreeze/cc-crossbeam, which has 293 GitHub stars. The repository holds 20 skills in this directory. The repository was last updated on March 2, 2026.

Source: mikeOnBreeze/cc-crossbeam on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.