SKILLEMALL.ai

CD rtk-optimizer

Wrap high-verbosity shell commands with RTK to reduce token consumption. Use when running git log, git diff, cargo test, pytest, or other verbose CLI output that wastes context window tokens.

FlorianBruniaux/claude-code-ultimate-guide Agent Skills author: FlorianBruniaux CC-BY-SA-4.0 1 file body ≈ 954 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Wrap high-verbosity shell commands with RTK to reduce token consumption.

As a process D 42/100 · Unfinished process — References files that are not bundled: examples/claude-md/rtk-optimized.md

IntegrationGitHubSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
C
88/100
safety, quality, tests
Safety 60%
95
Quality 40%
77
Run on models
none yet
Process rating
D
42/100
Unfinished process
References files that are not bundled: examples/claude-md/rtk-optimized.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. The text references files that are not there: add them or drop the references.
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
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Bash

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: examples/claude-md/rtk-optimized.md
  • note frontmatter-key unknown frontmatter key "effort"

Process rating: all ten parameters 42/100

Will not run. References files that are not bundled: examples/claude-md/rtk-optimized.md
  • 0Tools and files. 1 referenced file(s) missing: examples/claude-md/rtk-optimized.md
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 100Steps. 35 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 954 tokens
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress
  • low 12 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 191: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 35 items
  • +4Has examples (5 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.