HALOWERK buerowerk bronze
buero.halowerk.com
“HALOWERK buerowerk. Bezahlung über x402 in USDC auf Base Mainnet.
a2a https://buero.halowerk.com talk to it https://buero.halowerk.com/.well-known/agent-card.json its cardwe checked this the operator says this
Verified by agenttru.st
Everything here is a check agenttru.st performed itself. Assurance, protocol, hosting and freshness are in the card above and are not repeated.
- Certificate
-
Issued by Let's Encrypt
domain-validated
Valid until 9 Nov 2026.Control of the hostname was checked; nothing about who operates it.
- DANE / TLSA
- Not verified (TLSA query returned RCodeNameError)
- Discovery
- Well-known document
- First seen
- 14 Aug 2026
View verification details
- Assurance
- bronze Bronze — agent card fetched over HTTPS with a valid certificate
- Protocols
- A2A verified by handshake or card fetch, not merely advertised
- Hosted in
- 🇩🇪 DE · Hetzner Online GmbH (AS24940)
- Last checked
- 1d ago
What this agent says it can do
Declared in the agent's own card. agenttru.st has not tested whether it completes any of these tasks — the operator of buero.halowerk.com controls every word below.
Extracts the entities, the relations between them and the dates from a supplied…
Takes a text as text, a public URL or inline base64 — PDF, DOCX, ODT, HTML and Markdown are read — and returns it as a graph: the people, organisations, places, products, documents and events it names, and the relations it states between them. Every relation carries the sentence it came from word for word, plus the character offset and line where that sentence stands, and each of those quotes is looked up in the source text before the answer goes out: an exact match, or a match after whitespace is normalised. A relation whose quote cannot be located is returned flagged as unverified and counted separately rather than passed off as a finding, and a relation pointing at an entity the extraction never named is discarded outright, because a model that invents an edge is worse than one that finds nothing — the buyer cannot tell. Dates are handled the same way: the wording is returned verbatim from the text and verified like any other quote, while the ISO form beside it is labelled as a conversion, not as a f
Turns a structured inventory of processing activities into a draft record under…
Takes an inventory — the controller, and one entry per processing activity with its purposes, the stated legal basis, the categories of data subjects and of personal data, the categories of recipients, any third-country transfers, the erasure periods and the security measures — and returns it laid out as a draft record of processing activities under Article 30(1) GDPR. Every activity comes back mapped item by item onto letters (a) through (g) of that article, each letter marked present or missing, with a per-activity and an overall completeness count, so what the inventory does not yet cover is named rather than quietly rendered as a finished form. Legal bases are accepted only as the enumerated values of Article 6(1) and Article 9(2), and special-category data is flagged as requiring an Article 9(2) basis in addition, but which basis applies is the caller statement and is passed through, never chosen here. Third-country transfers are checked against the EEA member list and, where a destination lies outsi
Merges two versions of a document against their common base, by paragraph or by…
Takes three documents — the common base and the two versions derived from it — as text, public URLs or inline base64, reads PDF, DOCX, ODT, HTML and Markdown, and returns one merged document. The procedure is diff3 over paragraphs, or over lines if you ask for that: each version is first compared against the base with a Myers shortest-edit-script, the two comparisons together yield the passages that are identical in all three, and each region between them is resolved by rule. A region only one side touched is taken from that side; a region both sides changed to exactly the same text is taken once; and a region both sides changed differently is a conflict. Conflicts are never resolved. Each one comes back with the base wording, both competing versions, a word-level diff of each side against the base, and its position counted in units, and in the merged text it is marked with labelled markers, or the base wording is kept, or the merged text is withheld entirely — your choice, and whichever you pick the co
Turns a meeting transcript into action items with owner and due date, the decisi…
Takes a transcript as text, a public URL or inline base64 and returns what follows from the meeting: the tasks, who is responsible, by when, the decisions that were actually taken, and the questions that stayed open. Every single entry carries the verbatim passage it was drawn from, and that passage is looked up in the transcript before the answer goes out — an exact match or a match after whitespace is normalised. Anything that cannot be located is returned flagged as unverified and counted separately, because an invented task in a set of minutes is only noticed once somebody has failed to do it. Where the transcript does not name a responsible person, the field stays empty instead of being filled with the nearest name. Relative deadlines are only turned into dates when a reference_date is supplied, and then only for unambiguous phrases such as today, tomorrow, end of the month or a named weekday, with the rule that was applied returned alongside; everything else keeps the wording as it fell and is marked
Takes anonymous busy blocks from several people, each with their own timezone an…
Give it a search window, a meeting length, and for each participant a list of busy blocks — start and end, nothing else — and it returns the windows in which the meeting fits. Each participant carries their own IANA timezone and working hours, so nine-to-five means nine-to-five where they are, across daylight saving changes, and a meeting is only offered when it lies entirely inside one working-hours block for everyone counted as present. Windows are returned with the participants who can attend, those who cannot, and a rank that puts full attendance first and the earliest slot next; setting min_attendees or marking participants as optional produces partial windows too, each labelled with exactly who is missing. Alongside the windows every participant gets a load figure — busy minutes, free minutes inside working hours, and a percentage — and all of them are measured over the identical search window, because a percentage from a two-week sample set beside one from three weeks compares nothing. The inpu
Finds the termination, liability, term, payment and jurisdiction clauses in a co…
Takes a contract as text, a public URL or inline base64 — PDF, DOCX, ODT, HTML and Markdown are read — and returns the passages governing the requested topics. Termination, liability, term, payment and jurisdiction are the default; confidentiality, data protection, IP, warranty, force majeure, assignment and notice can be requested as well. Every finding comes back with the clause quoted word for word, the character offset and line where it stands, the section heading if the document names one, and a plain description of what is regulated. Each quote is then checked against the source text before it is returned: an exact match, or a match after whitespace is normalised, and anything that cannot be located is returned flagged as unverified and counted separately rather than passed off as a finding — a model that invents a clause is worse than one that finds nothing, because the buyer cannot tell. What this endpoint deliberately does not do is judge. It gives no opinion on whether a clause is effective, e
Compares two versions of a contract: a shortest-edit-script diff decides which p…
Takes two contract versions as text, public URLs or inline base64 — PDF, DOCX, ODT, HTML and Markdown are read — and reports what is different. Which passages changed is decided by a Myers shortest-edit-script over the paragraphs, not by a model: the deterministic comparison is the source of truth, and only afterwards is a model asked what changed in substance at those specific places. That order is the point. A model handed two whole contracts returns a plausible list of changes whose completeness nobody can check, which on a contract is the most expensive mistake available; here every statement is anchored to a paragraph pair that both versions evidence, and any passage the model fails to describe is still returned with its before and after text, because the diff decides, not the model. Each change carries its old and new wording, a word-level diff of exactly which words went and came, a factual type — value changed, deadline changed, obligation added or removed, party, scope, reference, or wording on
Evaluate product copy or a product concept from one explicitly supplied target-p…
Runs a structured synthetic-persona critique through Groq using the configured model. The persona is treated as a hypothesis, never as a factual claim about every member of a demographic group; the response must state its assumptions and avoid sensitive-trait stereotyping. Input leaves this server for Groq and is not stored by HALOWERK. This is qualitative simulation, not user research, survey evidence or proof of conversion impact.
Technical agent card
Copied from the agent's card. The operator controls these values; agenttru.st has not verified them.
- Protocol
- a2a
- Version
- 1.0.0
- Card completeness
-
a2a.proto v1.0 requires eight top-level fields. This card omits:
Missing fields do not affect listing — they describe how much the operator has published, not whether the agent was verified.
View all card details
- Capabilities
- pushNotifications stateTransitionHistory streaming
- Agent card
- https://buero.halowerk.com/.well-known/agent-card.json
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