SKILLEMALL.ai

AC cli-builder

Activate this skill whenever a user asks to build, design, or improve a command-line interface (CLI) tool. This includes: building CLIs in Node.js (Commander, yargs, oclif, Ink), Python (Click, Typer, argparse, Rich), Go (cobra, urfave/cli, bubbletea), or Rust (clap), argument parsing and validation, interactive prompts and TUI (terminal UI), output formatting (tables, colors, progress bars, spinners), configuration file management, shell completions, man pages, packaging and distribution (npm, PyPI, Homebrew, goreleaser, single-binary builds), plugin systems, and CLI testing strategies. Also activate for questions about terminal colors, ANSI escape codes, stdin/stdout piping, or cross-platform CLI behavior.

ClawHub Agent Skills author: royhk920 v1.0.0 MIT-0 5 files · 1 script body ≈ 3 182 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

IntegrationSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
99
Quality 40%
81
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Consistency w 8
40
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Dangerous commands cmd-shell-rc SKILL.md:406
      Writes to a shell startup file (documentation of a security skill)
      mytool completion bash >> ~/.bashrc
      security skill

    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 54/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 40Consistency. Frontmatter name (cli-builder) differs from the folder (ai-cli-builder)
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 24 steps
    • 100Execution cost. Instruction body is 3182 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress
    • low 10 top-level sections: this looks like several domains in one skill

    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)
    • +3Output format is not stated: the model decides each time
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 717: enough signal without eating the budget
    • +4Structure: 38 headings
    • +3Step-by-step instructions: 24 items
    • +4Has examples (24 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

    External checks

    ClawHub: clean
    This skill provides normal CLI-building guidance and optional scaffolding examples without hidden data access or unsafe automatic behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026