Dataset Viewer
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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
compilerOptions: struct<target: string, module: string, moduleResolution: string, strict: bool, skipLibCheck: bool, n (... 12 chars omitted)
  child 0, target: string
  child 1, module: string
  child 2, moduleResolution: string
  child 3, strict: bool
  child 4, skipLibCheck: bool
  child 5, noEmit: bool
include: list<item: string>
  child 0, item: string
name: string
license: string
type: string
description: string
scripts: struct<start: string, typecheck: string>
  child 0, start: string
  child 1, typecheck: string
devDependencies: struct<tsx: string, typescript: string>
  child 0, tsx: string
  child 1, typescript: string
engines: struct<node: string>
  child 0, node: string
dependencies: struct<@modelcontextprotocol/server: string, zod: string>
  child 0, @modelcontextprotocol/server: string
  child 1, zod: string
version: string
to
{'name': Value('string'), 'version': Value('string'), 'description': Value('string'), 'type': Value('string'), 'license': Value('string'), 'engines': {'node': Value('string')}, 'scripts': {'start': Value('string'), 'typecheck': Value('string')}, 'dependencies': {'@modelcontextprotocol/server': Value('string'), 'zod': Value('string')}, 'devDependencies': {'tsx': Value('string'), 'typescript': Value('string')}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              compilerOptions: struct<target: string, module: string, moduleResolution: string, strict: bool, skipLibCheck: bool, n (... 12 chars omitted)
                child 0, target: string
                child 1, module: string
                child 2, moduleResolution: string
                child 3, strict: bool
                child 4, skipLibCheck: bool
                child 5, noEmit: bool
              include: list<item: string>
                child 0, item: string
              name: string
              license: string
              type: string
              description: string
              scripts: struct<start: string, typecheck: string>
                child 0, start: string
                child 1, typecheck: string
              devDependencies: struct<tsx: string, typescript: string>
                child 0, tsx: string
                child 1, typescript: string
              engines: struct<node: string>
                child 0, node: string
              dependencies: struct<@modelcontextprotocol/server: string, zod: string>
                child 0, @modelcontextprotocol/server: string
                child 1, zod: string
              version: string
              to
              {'name': Value('string'), 'version': Value('string'), 'description': Value('string'), 'type': Value('string'), 'license': Value('string'), 'engines': {'node': Value('string')}, 'scripts': {'start': Value('string'), 'typecheck': Value('string')}, 'dependencies': {'@modelcontextprotocol/server': Value('string'), 'zod': Value('string')}, 'devDependencies': {'tsx': Value('string'), 'typescript': Value('string')}}
              because column names don't match

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

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RiskUnit.md

Prenosljiv, agentsko berljiv osebni kontekstni profil („podatkovno sledstvo") v obliki .md datoteke, ki ga generira AI agent na podlagi osebnih podatkov in potreb uporabnika iz Evropske denarnice (EUDI eWallet), shranjuje ga uporabnik v denarnici, konzumirajo pa ga agenti (OpenClaw, Cursor, CLI, IDE) kot custom system prompt / kontekst prek MCP storitve.

Lastnosti: #immutable (podpisan, append-only sistem zapisov) · #interoperable (odprt markdown, ki ga bere vsak agentni .md mehanizem) · delegated issuer (obsege dostopa izdaja izdajatelj, ne agent).

v0.2 — zavarovalniška perspektiva: RiskUnit.md kot tržni predmet (podatki kot produkt), MCP kot agency sloj med denarnico in zavarovalnicami; agent kupuje zavarovalne storitve in uveljavlja odškodnine — glej INSURANCE_PROSPECTIVE.md.

Vsebina repozitorija

Datoteka Opis
PRD.md Product Requirements Document — problem, osebe, zahteve, MVP, merila uspeha
skills.md Agent Skill risk-unit-profile v formatu Agent Skills (SKILL.md)
MCP.md Specifikacija MCP storitve risk-unit-mcp — orodja, viri, avtorizacija, konfiguracija
TECHNICAL_SPECIFICATION.md Tehnološka specifikacija — arhitektura, podatkovni format, orkestracija, sklad
INSURANCE_PROSPECTIVE.md v2 zavarovalniška perspektiva — MCP kot agency sloj, podatki kot produkt, nakup poliz in odškodnine
mcp-server/ Delujoč prototip MCP strežnika (TypeScript, stdio, mock profil, v0.2 z zavarovalniško plati)

Hiter start — prototip MCP strežnika

cd mcp-server
npm install
npm start

Strežnik teče prek stdio. Preizkus z MCP inspectorjem:

npx @modelcontextprotocol/inspector npm start

Kontekst nastanka

Izklesano iz brainstorm zapiskov (Risk Unit .md): turistična datoteka v Evropski denarnici kot »podatkovno sledstvo« za tveganja; OpenClaw / Cursor / CLI / IDE vsi uporabljajo .md datoteke; #immutable, #interoperable → sistem zapisov, delegated issuer; profil v eWalletu, obdelan s strani agenta, kot custom system prompt (bančno/finančno + ads).

Status

Draft v0.2 — konceptualna specifikacija + prototip z mock profilom, podpisi in polizami. EUDI denarnica, podpisovanje Ed25519, OIDC4VP/OIDC4VCI in attestation celovitosti razkritja so v prototipu mockirani.

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