Agent skill

Demo City Review

by mikeOnBreeze in mikeOnBreeze/cc-crossbeam

Local demo: City-side ADU plan review. An agent skill from mikeOnBreeze/cc-crossbeam.

MITAuto-check passedAgent Workflows

Install Demo City Review

skills CLI
$ npx skills add mikeOnBreeze/cc-crossbeam --skill demo-city-review -a claude-code

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

GitHub CLI
$ gh skill install mikeOnBreeze/cc-crossbeam demo-city-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/.claude/skills/demo-city-review .claude/skills/demo-city-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
demo-city-review
GitHub stars
293
Token cost
~1.8k tokens
SKILL.md length
778 words
Files
1
Skills in repo
20
Repo updated
First seen
Licence
MIT

At a glance

Local demo: City-side ADU plan review. An agent skill from mikeOnBreeze/cc-crossbeam.

  • Works in 5 steps: Sheet Manifest (~30-90 sec) → Sheet-by-Sheet Review (~3-5 min) → Code Verification (concurrent, ~60-90 sec) → …
  • : Review this ADU plan set for [City]
  • SKILL.md covers How to Invoke, Input Resolution, Output Directory and Workflow, plus 3 more sections
  • Calls pdftoppm and brew

What it does

Demo City Review is an agent skill from mikeOnBreeze/cc-crossbeam. Local demo: City-side ADU plan review. Point this at a plan binder (PDF or pre-extracted PNGs) and a city name. It reviews the plans sheet-by-sheet against state and city code, then generates a draft corrections letter. Fire-and-forget — no human-in-the-loop pause. Triggers on: 'Review this ADU plan set for [City]' or 'Run the city review on [path]'.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Human-in-the-loop approvals and 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

  • : Review this ADU plan set for [City]
  • Run the city review on [path]

Example prompts

  • “Review this ADU plan set for [City]”
  • “Run the city review on [path]”
  • “/demo-city-review”

Workflow steps

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

  1. Sheet Manifest (~30-90 sec)
  2. Sheet-by-Sheet Review (~3-5 min)
  3. Code Verification (concurrent, ~60-90 sec)
  4. Draft Corrections Letter (~2 min)
  5. Present Results

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

    Shell commands in SKILL.md call:

    • pdftoppm
    • brew

    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

Demo City Review loads about 1.8k tokens when it runs. Until then it costs about 92 tokens; SKILL.md has 778 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~92
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k

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). 778 words, ~1,773 tokens.

Download SKILL.mdSave it as .claude/skills/demo-city-review/SKILL.md (or your agent's skills folder).
name
demo-city-review
description
Local demo: City-side ADU plan review. Point this at a plan binder (PDF or pre-extracted PNGs) and a city name. It reviews the plans sheet-by-sheet against state and city code, then generates a draft corrections letter. Fire-and-forget — no human-in-the-loop pause. Triggers on: 'Review this ADU plan set for [City]' or 'Run the city review on [path]'.

Demo: City Plan Review

Run a city-side ADU plan review locally. You are a city plan checker reviewing an ADU permit submittal for code compliance.

How to Invoke

The user provides:

  1. Plan binder — either a PDF path or a directory of pre-extracted PNGs
  2. City name — e.g., "Placentia", "Buena Park", "Long Beach"
  3. (Optional) Project address

Example invocations:

  • "Review this ADU plan set for Placentia: test-assets/city-flow/mock-session/pages-png/"
  • "Run city review on test-assets/01-extract-test/pages-png/ for Buena Park"
  • "Review path/to/plans.pdf for the City of Long Beach"

Input Resolution

Determine what the user gave you:

If a directory of PNGs (e.g., pages-png/page-01.png, page-02.png, ...):

  • Use directly. Skip PDF extraction.
  • Check for pre-existing sheet-manifest.json in the same directory or parent. If found, load it and skip manifest building.
  • Check for pre-existing title-blocks/ directory. If found, use those for manifest building.

If a PDF file:

  • Check if pdftoppm is installed: which pdftoppm
  • If not: brew install poppler (macOS) or tell the user to install it
  • Extract pages: create a pages-png/ directory next to the PDF and run:
    pdftoppm -png -r 200 "<input.pdf>" "<output-dir>/pages-png/page"
  • Rename outputs to page-01.png, page-02.png, etc. (pdftoppm outputs page-01.png format already with the prefix)

Output Directory

Create demo-output/city-review-<city>-<timestamp>/ in the workspace root. All output files go here.

Workflow

Phase 1: Sheet Manifest (~30-90 sec)

Follow the adu-targeted-page-viewer skill workflow:

  1. Read page 1 (cover sheet) visually. Extract the sheet index.
  2. If page count matches index count, map 1:1 in order.
  3. If mismatch, read title blocks to resolve (crop bottom-right 20% of each page, or use pre-cropped title blocks if available).
  4. Write sheet-manifest.json to the output directory.
Phase 2: Sheet-by-Sheet Review (~3-5 min)

Review sheets in parallel using subagents. Group by discipline:

Subagent A — Administrative + Architectural:

  • Cover sheet (CS): stamps, signatures, governing codes list, sheet index accuracy, project data
  • Floor plan (A-series): room dimensions, fixture counts, egress, accessibility

Subagent B — Site + Civil:

  • Site plan: setbacks, lot coverage, FAR, parking, utility connections shown, easements
  • Grading/drainage: slopes shown, drainage direction, "For Reference Only" stamp

Subagent C — Elevations + Fire/Life Safety:

  • Elevations: height compliance, fire separation distance (< 5' from property line = 1-hour rated), roof plan consistency
  • Building sections: insulation, foundation-to-wall connection

Launch all three concurrently. Each subagent reads the relevant PNGs and produces findings.

For each finding, record:

  • check: What was checked
  • status: PASS | FAIL | UNCLEAR | NOT_APPLICABLE
  • confidence: HIGH | MEDIUM | LOW
  • observation: What was actually seen on the plan
  • code_ref: Code section (CRC, CBC, Gov. Code, municipal code)
  • sheet_id and page_number

Write all findings to sheet_findings.json.

Phase 3: Code Verification (concurrent, ~60-90 sec)

Launch two parallel subagents:

3A — State Law Verification:

  • Load reference files from adu-skill-development/skill/california-adu/references/
  • For each FAIL and UNCLEAR finding, verify the code citation
  • Check for ADU-specific exceptions (Gov. Code § 66310-66342)
  • Write state_compliance.json

3B — City Rules:

  • Check if adu-skill-development/skill/<city-slug>-adu/ exists
    • If yes (onboarded city): Load the city skill reference files. Fast, offline.
    • If no: Run the adu-city-research skill — Discovery (WebSearch) then Extraction (WebFetch)
  • Check findings against city-specific amendments, standard details, IBs
  • Write city_compliance.json
Show full SKILL.md (295 more words)Show less
Phase 4: Draft Corrections Letter (~2 min)

Merge all inputs and generate the corrections letter:

  1. For each finding, apply the filter:

    • Confirmed by code → include with citation
    • Confirmed but LOW visual confidence → include with [VERIFY] flag
    • No code basis found → drop it (no false positives)
    • Structural/engineering adequacy → [REVIEWER: ...] blank for human
    • Subjective judgment → drop it (prohibited for ADUs per Gov. Code § 66314(b)(1))
  2. Write two outputs:

    • draft_corrections.json — structured, each item with code citation, confidence, reviewer_action
    • draft_corrections.md — formatted markdown corrections letter ready to read
  3. Write review_summary.json — stats on items found, confidence breakdown, coverage

Phase 5: Present Results

After all phases complete, present to the user:

  • Summary: how many items found, confidence breakdown
  • The full draft_corrections.md content
  • Note which items need [VERIFY] or [REVIEWER] attention
  • List output files written

Key Rules

  • No false positives. Drop findings without code basis. It's better to miss something than to flag something incorrectly.
  • Reviewer blanks > AI guesses. For structural and engineering items, use [REVIEWER: ...] instead of guessing.
  • Objective standards only. ADUs can only be subject to objective, measurable standards (Gov. Code § 66314(b)(1)). Never flag subjective design issues.
  • State preemption. If a city rule is more restrictive than state law, flag the conflict — state law prevails.
  • Two confidence dimensions. Report both code confidence (is this legally required?) and visual confidence (am I correct about what I see?).

Test Data

Ready-to-use test data for demos:

Test SetCityPath
1232 N JeffersonPlacentiatest-assets/city-flow/mock-session/pages-png/ (15 pages, title blocks in ../title-blocks/)
Same projectPlacentiatest-assets/01-extract-test/pages-png/ (15 pages, same project)

Pre-built mock session data (for comparison): test-assets/city-flow/mock-session/sheet-manifest.json

Sub-Skills Referenced

SkillLocationRole
adu-targeted-page-vieweradu-skill-development/skill/adu-targeted-page-viewer/PDF extraction + sheet manifest
california-aduadu-skill-development/skill/california-adu/State law (28 reference files)
adu-city-research.claude/skills/adu-city-research/Web research for non-onboarded cities
placentia-aduadu-skill-development/skill/placentia-adu/Placentia-specific rules (onboarded)
buena-park-aduadu-skill-development/skill/buena-park-adu/Buena Park-specific rules (onboarded)

© 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

Just SKILL.md in .claude/skills/demo-city-review of mikeOnBreeze/cc-crossbeam.

Open the folder on GitHubat commit cc5591e

Compare with similar skills

Demo City Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Demo City Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Demo City Review this skillmikeOnBreeze/cc-crossbeam293—~1.8kAutomated safety check: PassMIT
Cv BuilderLeoYeAI/openclaw-master-skills2.2k—~2.7kAutomated safety check: PassMIT
Build With SimplepdfSimplePDF/simplepdf-embed407—~7kAutomated safety check: PassMIT
Plannotator Annotatebacknotprop/plannotator9.3k—~413Automated safety check: PassApache-2.0
Workflow AutomationJoelLewis/finance_skills206—~7.3kAutomated safety check: PassMIT
Agent UIaiskillstore/marketplace4331 repos~883Automated safety check: NotesNone

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Questions about Demo City Review

What does Demo City Review do?

Local demo: City-side ADU plan review. An agent skill from mikeOnBreeze/cc-crossbeam. Demo City Review is an agent skill from mikeOnBreeze/cc-crossbeam. Local demo: City-side ADU plan review.

When should I use Demo City Review?

Demo City Review fits situations like: : Review this ADU plan set for [City]; run the city review on [path].

How do I install Demo City Review in Claude Code?

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

How do I install Demo City Review in Codex?

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

Can I use Demo City 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 demo-city-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/demo-city-review, .gemini/skills/demo-city-review, .github/skills/demo-city-review and .opencode/skills/demo-city-review in your project.

What does Demo City Review need to run?

Going by SKILL.md and its folder, Demo City Review needs the command-line tools its instructions call (pdftoppm and brew).

Does Demo City 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 Demo City 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 Demo City Review use?

Demo City 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 Demo City Review use?

About 1.8k tokens (SKILL.md is roughly 7.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Demo City Review?

Skills that share tags, products or a category with Demo City Review: Cv Builder (LeoYeAI/openclaw-master-skills, 2.2k stars), Build With Simplepdf (SimplePDF/simplepdf-embed, 407 stars), Plannotator Annotate (backnotprop/plannotator, 9.3k stars) and Workflow Automation (JoelLewis/finance_skills, 206 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Demo City 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.