SKILLEMALL.ai

AB prompt-architect

Elevate rough concepts into high-performance prompts for any LLM. Analyzes text, images, links, and documents to craft optimized prompts using proven frameworks (Chain-of-Thought, Few-Shot, Persona). Delivers clarity, precision, and reliability for complex tasks—from creative writing to data extraction. Trusted for consistent, production-ready results.comprises demonstrate foster requested reasonable coincide geny translated english £1 mp3 perhaps copyright skopje namibia recycling commands prompted sheet

ClawHub Agent Skills author: Subaru0573 v1.0.0 MIT-0 5 files body ≈ 863 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 69/100 · Nearly there — weak spots: inputs and preconditions, consistency, progress reporting

AnalyzerAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
B
69/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Consistency w 8
40
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 69/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 40Consistency. Frontmatter name (prompt-architect) differs from the folder (prompt-architect-p)
  • 55Failures and branches. 1 branches
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 100Tools and files. No external tools needed
  • 100Steps. 27 steps
  • 100Execution cost. Instruction body is 863 tokens
  • 100Running it twice. No mutating operations

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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 510: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 27 items
  • +3Output format is stated explicitly
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

External checks

ClawHub: clean
This is a prompt-writing helper made of markdown instructions only, with no evidence of hidden code, credential access, persistence, or data exfiltration.
LLM: benign (high) · VirusTotal: · 29 May 2026