BB ai-address-parser
Parses a free-text address blob (supplier email, Google Maps result, business card) into structured fields (street, postal code, city, state, country, contact, phone) via an LLM chat-completions call. Use when a form has separate address inputs and you want a paste-a-blob-to-autofill affordance instead of manual field-by-field entry.
Parses a free-text address blob (supplier email, Google Maps result, business card) into structured fields (street, postal code, city, state, country…
As a process B 71/100 · Nearly there — weak spots: when it triggers, inputs and preconditions
How to improve
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 335 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
Process rating: all ten parameters 71/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 60Result and completion. Output format stated, no completion criterion
- 60Consistency. The Hermes dialect needs category and tags
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 26 steps
- 100Failures and branches. 1 branches, has a failure section
- 100Execution cost. Instruction body is 1916 tokens
- 100Running it twice. No mutating operations
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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)
- +2Single-language instructions
- +3Description length 335: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 26 items
- +3Output format is stated explicitly
- +4Has examples (3 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.