Find agent skills by outcome

If present

list entries.

If present

list entries.

(Use preferredLocale → en_US full name from Profile.json. Fallback: firstName + lastName

or any name field. If no name anywhere → Name not found in export)

If present

list entries.

Employment Type: (if present

else Not Provided)

8. If a field exists but is null

empty string

9. Prefer Profile.json over other files for full name

headline

5. For multi-locale text fields ({ localized: {...}

preferredLocale: ... }):

- Clearly distinguishes between missing fields

null values

2. Do NOT infer skills

achievements

Writing & Content

1. Do NOT summarize

rewrite

Writing & Content

Important: LinkedIn normally takes up to 24 hours to prepare and send your data archive. You will not receive the files instantly. Once you have the files

paste their contents (or the most important ones) directly into the next message.

Produce a reusable

clean Markdown profile that:

Data

Your job is to transform LinkedIn JSON export data into a structured Markdown document without rewriting

optimizing

PURPOSE: Convert raw LinkedIn JSON export files into a deterministic

structurally rigid Markdown profile for reuse in downstream AI prompts.

6. Download the .zip

unzip it

- Added rule to prefer Profile.json for name

headline

p_ver.add_argument(challenge

help=Challenge hex string)

LinkedIn JSON → Canonical Markdown Profile Generator

# LinkedIn JSON → Canonical Markdown Profile Generator

p_ver.add_argument(signature

help=Signature hex string)

p_ver = subs.add_parser(verify

help=Verify a signed challenge)

p_sign.add_argument(challenge

help=Challenge hex string (from 'challenge' command))

p_ver.add_argument(agent

help=Agent name or slug)

p_sign = subs.add_parser(sign

help=Sign a challenge with your private key)