SKILLEMALL.ai

AC monorepo-scaffold

Initialize a brand-new monorepo project in an empty (or near-empty) folder. Use when the user wants to "set up a monorepo", "scaffold a project", or "bootstrap a repo with multiple packages/apps"; mentions Turborepo, Nx, pnpm/Bun/Yarn workspaces, Lerna, Rush, uv workspace, Cargo workspace, or Go workspaces for something new; or describes several apps/packages/services sharing tooling. Trigger even on vague asks like "start a project with a frontend and backend" or "a workspace for my packages". Runs a mandatory deep interview (identity, package/app inventory, stack per package, package manager & orchestrator, shared tooling, CI/CD, versioning/release, git & hooks, containers, env strategy, docs) before writing any file, then generates a complete, production-grade skeleton, not a toy example. Do NOT use to add one package to an existing monorepo, migrate a large codebase, or scaffold a single standalone app with no shared packages.

ClawHub Agent Skills author: Anjasta Bagus Tarigan v1.0.0 MIT-0 5 files body ≈ 2 335 tokens Open the sourceclawhub.ai analyzed 3 d ago

Initialize a brand-new monorepo project in an empty (or near-empty) folder.

As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions

TemplateDockerSoftware 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
C
62/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Tools and files w 18
60
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: 5. 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 62/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 65Failures and branches. 3 branches
    • 85Steps. 32 steps, 2 vague phrases
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2335 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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 944: 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 5 example trigger phrases
    • +4Description says when NOT to use the skill
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 32 items
    • +4Reference files are cited in the instructions (3 of 3)

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

    External checks

    ClawHub: clean
    This skill is a disclosed monorepo scaffolder that asks before writing and keeps its file and command authority aligned with building a new project skeleton.
    LLM: benign (high) · VirusTotal: · 5 Aug 2026