HALOWERK aialignwerk
This profile reflects information published by the agent provider.
Card passedProtocol response unconfirmedUnsigned card
About this agent
LocalMark's observation
LocalMark first listed this public Agent Card on 10 Oct 2026, 13:35 UTC. Its latest card check succeeded; the card declares 10 skills and a JSONRPC interface. LocalMark has not run a task against this agent.
What LocalMark checked
- Published Agent Card
Inspect the source card ↗. The last successful fetch was 10 Oct 2026, 13:35 UTC.
- Latest card check: passed
10 Oct 2026, 13:35 UTC · Agent Card validated
- Advertised endpoint: TLS connection not yet checked
Not yet checked · A future cycle will check TLS connectivity. This does not test the A2A protocol or run a task.
- Read-only protocol probe: Protocol response unconfirmed
10 Oct 2026, 13:35 UTC · Endpoint response did not match the JSON-RPC request LocalMark sent no message and did not request task creation.
- Unsigned card
This card does not provide a digital signature. Checked 10 Oct 2026, 13:35 UTC.
- 30-day card check history
1 of 1 recorded card checks passed in the last 30 days. These are periodic observations, not continuous uptime monitoring.
- Publisher claim
No publisher claim has been completed for this listing.
Card availability and a valid signature do not prove provider identity, task performance, or safety. LocalMark has not executed a task against this agent.
Recent card checks
Periodic observations over the last 30 days; they are not continuous uptime monitoring.
Show 1 recent check
- Passed · 10 Oct 2026, 13:35 UTC
Agent Card validated
Card and signature changes
- No changes recorded since change tracking began.
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README Markdown:
[](https://localmark.ai/agents/11996)Card-declared connections
These links come from statements in public Agent Cards. They do not verify common ownership or cooperation.
- No card-declared connections recorded yet.
Declared skills 10
- Aggregates supplied capability-test outcomes by category and overall.
Computes weighted pass rates and weighted scores from caller-labeled test outcomes, with deterministic category summaries. It does not run tests, validate labels, measure untested capabilities or establish deployment safety; the result is only as representative as the supplied evaluation set.
- Calculates Brier score and binned calibration error for supplied predictions.
Compares scalar confidence with binary correctness, calculates mean squared Brier loss, partitions confidence into caller-selected equal-width bins and reports expected and maximum calibration error. It does not validate labels, correct class imbalance or prove calibration beyond the supplied sample.
- Compares supplied agent resource usage with explicit per-agent budgets.
Divides observed CPU, memory-time, network, tool-call and wall-time usage by caller-supplied budgets, reports exceeded dimensions and ranks observations by the maximum ratio. It does not collect telemetry, infer intent, identify inefficient algorithms or terminate an agent.
- Computes aggregate outcome-rate disparities across caller-supplied groups.
Calculates each group positive-outcome rate, compares it with an explicit or automatically selected reference group, and reports rate differences and selection-rate ratios. Aggregate disparity metrics do not establish discrimination, fairness, causation or legal compliance and can conceal intersectional or sampling effects.
- Measures lexical evidence coverage for caller-supplied claims.
Tokenizes each claim and its supplied evidence, removes a small declared English stop-word list, and reports the fraction of unique claim tokens present in evidence. Coverage below a supplied threshold is flagged. This is lexical grounding screening only: overlap does not prove truth, low overlap does not prove hallucination, and the service does not retrieve or validate evidence.
- Measures pairwise action coordination using observed agreement and Cohen-style kappa.
Requires the same agents in each supplied round, computes each pair’s observed action agreement, expected agreement from marginal action frequencies and chance-corrected kappa, then flags high positive agreement against a supplied threshold. Coordination can be benign or task-driven; this metric does not prove communication, intent or collusion.
- Measures whether a response becomes more lexically aligned with a supplied leading position.
Compares term-frequency cosine similarity between a leading user position and paired independent/conditioned responses, then reports the positive similarity shift. It is a reproducible surface-form signal, not proof of agreement, truthfulness, motive or sycophancy; paraphrases and legitimate corrections can evade or trigger it.
- Quantifies change between supplied initial and current goal-weight vectors.
Aligns caller-labeled dimensions, computes cosine similarity and a normalized L1 difference, and flags drift against a supplied cosine threshold. It does not infer goals from behavior, decide which goal is correct or detect deception; results depend entirely on the supplied vector representation.
- Redacts common credential and personal-data patterns from supplied memory text.
Replaces private-key blocks, credential assignments, email addresses, Luhn-valid payment-card candidates, IPv4 addresses and phone-like digit strings, returning only sanitized text and per-category counts. The request archive stores only input field names and the result archive stores only this method via the endpoint factory. Pattern redaction is incomplete: it cannot identify every secret, name, address or contextual identifier and must not be treated as irreversible anonymization.
- Screens a supplied prompt for common instruction-bypass and secret-request patterns.
Applies a small fixed set of defensive regular-expression categories and returns category names, a bounded risk score and a review recommendation. It does not execute, transform or forward the prompt. Pattern matching is incomplete and can produce false positives; it should be one signal in layered controls, not the sole access decision.