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AC adu-pdf-extraction

This skill extracts construction PDF plan binders into agent-consumable formats. It should be used when a contractor or homeowner provides a PDF binder of construction plans (site plans, floor plans, structural drawings, Title 24 reports) that needs to be parsed for permit review, corrections response, or plan check analysis. Produces three outputs: page PNGs for vision analysis, structured markdown per page via vision extraction, and a JSON manifest for routing.

mikeOnBreeze/cc-crossbeam Agent Skills author: mikeOnBreeze MIT 9 files · 2 scripts body ≈ 4 858 tokens Open the sourcegithub.com↗ analyzed 6 d ago

This skill extracts construction PDF plan binders into agent-consumable formats.

As a process C 63/100 · Has gaps — weak spots: inputs and preconditions, running it twice

ProcedureAI and agentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
94
Run on models
none yet
Process rating
C
63/100
Has gaps
Inputs and preconditions w 11
0
Running it twice w 4
30
When it triggers w 12
50
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note edit-residue the text marks something as outdated (lines 427, 429): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 63/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 3 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Execution cost. Instruction body is 4858 tokens
    • 85Steps. 92 steps, 2 vague phrases
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Progress reporting. Reports progress

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +3Description length 467: enough signal without eating the budget
    • +4Structure: 29 headings
    • +3Step-by-step instructions: 92 items
    • +3Output format is stated explicitly
    • +4Has examples (6 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +3All 2 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 94.