SKILLEMALL.ai

AB masterplan-builder

Build a complete, production-ready masterplan for a new project/system from scratch (0 to 100%) — websites, web apps, mobile apps, local AI assistants/agents, desktop apps, backend/APIs, browser extensions, CLI tools, etc. Use whenever the user wants to plan, design, or scope a new project/product before or instead of writing code — e.g. "help me plan/build/design a [website/app/assistant]", "I want to create a project for X", "buatkan masterplan untuk...". Not for reviewing an existing plan (use dev-plan-reviewer) or quick one-off scripts. Interviews the user topic by topic (name, users, tech stack, features, database, frontend/backend integration, and more, down to the smallest detail), researches current best options live on the web for every major decision instead of relying on stale training knowledge, and outputs a markdown masterplan saved to docs/masterplan/ in the project directory — detailed enough that code built from it is production-ready, nothing left at prototype quality.

ClawHub Agent Skills author: Anjasta Bagus Tarigan v1.0.0 MIT-0 7 files body ≈ 2 526 tokens Open the sourceclawhub.ai analyzed 2 d ago

Build a complete, production-ready masterplan for a new project/system from scratch (0 to 100%) — websites, web apps, mobile apps, local AI assistants/agents…

As a process B 78/100 · Nearly there — weak spots: result and completion, inputs and preconditions

GeneratorSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
B
78/100
Nearly there
Inputs and preconditions w 11
0
Result and completion w 14
40
Steps w 15
85
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: 0. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 78/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 40Result and completion. Does not say what the result is
    • 85Steps. 11 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2526 tokens
    • 100Running it twice. Mutating operations check current state
    • 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

    • +3Description length 1001: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • -5TODO / placeholder text left in the skill
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 3 example trigger phrases
    • +4Description says when NOT to use the skill
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 11 items
    • +4Reference files are cited in the instructions (4 of 4)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: clean
    This is a disclosed project-planning skill that researches, interviews the user, and writes a masterplan file, with a caveat that users should watch for unintended overwrites in docs/masterplan.
    LLM: benign (high) · VirusTotal: · 25 Jul 2026