BC 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
Elevate rough concepts into high-performance prompts for any LLM.
As a process C 61/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, consistency
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 61/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 40Consistency. Frontmatter name (prompt-architect) differs from the folder (prompt-architect-p)
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 85Steps. 27 steps, 1 vague phrases
- 100Tools and files. No external tools needed
- 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.