SKILLEMALL.ai

BB prompt-refiner

Transforms casual or voice-transcribed user requests into precise, AI-optimized prompts. Handles mixed languages, vague input, and ambiguity. Reduces task execution time by 2-3x and improves accuracy by 40-60%. Applies prompt engineering best practices including persona assignment, few-shot examples, chain of thought, and prompt chaining.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: jamesxu81 v1.0.1 MIT-0 7 files body ≈ 896 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 71/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, consistency

GeneratorAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
82
Quality 40%
88
Run on models
none yet
Process rating
B
71/100
Nearly there
Progress reporting w 2
0
When it triggers w 12
20
Inputs and preconditions w 11
30
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
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

  • high Dangerous commands cmd-persistence README.md:64
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    Context: macOS, running via LaunchAgent at ~/Library/LaunchAgents/...

Files scanned: 7. 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 71/100

  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Inputs and preconditions. Does not say what the process needs to start
  • 40Consistency. Frontmatter name (prompt-refiner) differs from the folder (covert-native-language-to-ai-firendly-prompt)
  • 55Failures and branches. 1 branches
  • 100Tools and files. No external tools needed
  • 100Steps. 27 steps
  • 100Result and completion. Output format and completion criterion are stated
  • 100Execution cost. Instruction body is 896 tokens
  • 100Running it twice. Mutating operations check current state

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)
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 340: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 27 items
  • +3Output format is stated explicitly
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

External checks

ClawHub: clean
This appears to be a prompt-rewriting skill with documentation hygiene issues, not a skill that itself accesses accounts or sends data externally.
LLM: benign (medium) · VirusTotal: · 29 May 2026