Find agent skills by outcome

8. If a field exists but is null

empty string

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

preferredLocale: ... }):

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

headline

- Clearly distinguishes between missing fields

null values

2. Do NOT infer skills

achievements

Writing & Content

1. Do NOT summarize

rewrite

Data

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

optimizing

Produce a reusable

clean Markdown profile that:

Writing & Content

Important: LinkedIn normally takes up to 24 hours to prepare and send your data archive. You will no...

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

PURPOSE: Convert raw LinkedIn JSON export files into a deterministic

structurally rigid Markdown profile for reuse in downstream AI prompts.

- Added rule to prefer Profile.json for name

headline

6. Download the .zip

unzip it

LinkedIn JSON → Canonical Markdown Profile Generator

pver.addargument(signature

help=Signature hex string)

pver.addargument(challenge

help=Challenge hex string)

pver = subs.addparser(verify

help=Verify a signed challenge)

psign.addargument(challenge

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

pver.addargument(agent

help=Agent name or slug)

psign = subs.addparser(sign

help=Sign a challenge with your private key)

pchal.addargument(agent

help=Agent name or slug to challenge)

pchal = subs.addparser(challenge

help=Create a challenge for another agent)

plook.addargument(agent

help=Agent name or slug (e.g. MRBIGCLAW or mp-ae72beed6b90))

plook = subs.addparser(lookup

help=Look up an agent by name or slug)

subs.add_parser(claim-url

help=Print claim URL for human owner)