DataPulse

Use for discovery only: find DataPulse's 440 Malaysian public datasets by topic, source, or licence—for example, 'Malaysian public data inflation', licence and attribution, or a government dataset source. Returns ranked matches with id, title, source, licence, published status, and score. This is not trust verification: a status is published pipeline context, not proof that a dataset is current

Return full detail for one dataset id, including its latest health status and last-verified timestamp, content_freshness_date, and freshness_signal_source (last_modified, content_parse, or none). Use to fetch the provenance/citation metadata for a dataset found via search_datasets and distinguish unknown-freshness from proven stale data. Use it for one dataset's current published detail; do not us

Return one bounded, machine-readable Dataset Passport v1 for a canonical dataset ID. It reads the published Passport artifact only; it does not fetch an upstream source or create evidence. The Passport describes observed metadata and evidence availability, not semantic truth, completeness, certification, legal permission, safety, or AI admission. Use it for the bounded Passport artifact; do not us

Return datasets whose status is aging, stale, or degraded, plus datasets missing from the latest health snapshot. Use when an agent needs to know which data has a freshness or schema-validity risk. Use it to enumerate freshness or schema-risk candidates; do not use it for anomalies, trends, reliability, or drift—use find_anomalies, find_deteriorating, find_unreliable, or find_schema_drift instea

Return datasets flagged by the latest published anomaly detection (anomalies), ranked by how far the observed update interval exceeds its threshold. Optionally require a minimum publish-reliability grade; includes pipeline-computed anomaly and reliability evidence so agents do not recompute it. Use it for unusual update intervals; do not use it for worsening freshness, recovery, reliability grades

Return datasets whose published freshness trend is deteriorating, ranked by staleness slope. Optionally require a minimum historical anomaly rate; includes pipeline-computed trend and reliability evidence so agents do not recompute it. Use it for worsening freshness trends; do not use it for anomalies, recovery, reliability grades, or structural drift—use find_anomalies, find_recovering, find_un

Return datasets whose published freshness trend is recovering, with the fastest staleness reductions first. Includes pipeline-computed trend and publish-reliability evidence. Use it for improving freshness trends; do not use it for deterioration, anomalies, reliability grades, or structural drift—use find_deteriorating, find_anomalies, find_unreliable, or find_schema_drift instead. It reads prec

Return datasets whose evaluated publish-reliability grade is at or below a threshold (the unreliable ones), with the worst grades and lowest on-time percentages first. Reliability measures timeliness of successful freshness observations, not uptime; sample days are included so agents can judge evidence depth. Use it for timeliness reliability grades; do not use it for individual anomalies, trends,

Return datasets with published structural or record-count drift evidence, ranked with structural changes first. Optionally require a minimum number of structural transitions; includes pipeline-computed evidence so agents do not infer drift from freshness alone. Use it for structural or record-count changes; do not use it for freshness risk, anomalies, trends, or reliability—use find_stale, find_

Return the published cross-source reconciliation group for a dataset name or id, including per-member counts, dates, statuses, tolerances, and contextual deltas. A discrepancy requires human review and does not prove either source is wrong. Use it to compare a dataset with its published cross-source group; do not use it for provenance or evidence receipts—use get_provenance or get_evidence inste

Use when asked 'can I cite this source?', for licence and attribution, or for citation-ready provenance. Returns source, steward, licence/attribution context, canonical URL, and compact published evidence context: probe time, transport, access dependency, freshness signal, schema drift / record-count drift context, anomaly flag, and status. Bind a citation to dataset identity, source/evidence URL,

Use for a deep evidence audit or to inspect a provenance and evidence receipt. Returns the complete published evidence receipt for one dataset: probe time, transport, access dependency, freshness, schema drift / record-count drift, tolerance, status, anomaly fields, and receipt/evidence references. It reads published pipeline evidence, not a live source fetch: you may report what the pipeline obse

This is the preferred single-call pre-trust check for 'is this dataset current?', stale, unknown-freshness, degraded, or browser-dependent questions, and whenever an agent must verify before relying on data. Returns dataset metadata, published evidence and fail-closed signed receipt verification with artifact references. It verifies published artifacts, not a live source check: you may infer wheth

Return a freshness-at-a-glance summary of the published catalogue: fresh, aging, stale, and reference counts plus the latest health check time. Use it for catalogue-level freshness context; do not use it to enumerate affected datasets—use find_stale instead. It reads the latest published snapshot, so missing counts or check time mean the artifact omitted them; DataPulse is read-only, requires no

Use when a fresh, rate-limited live-vs-published comparison is needed for a direct-access dataset, for example after asking whether a government dataset is reachable now. Performs a rate-limited live GET and returns comparable transport receipts plus a match, mismatch, unreachable, or not_verifiable verdict. This live check is an observation, not semantic truth: it does not recompute content dates

Return published attestation facts, the unsigned methodology-versioned trust score, numeric components, and component_availability reasons, plus existing health/trend/drift/reconciliation evidence for one canonical dataset id, e.g. 'fuelprice'. This tool does not re-probe or verify the signature; call verify_attestation separately. Use it to assemble the published trust view; do not use it for rec

Use to verify a signed published probe attestation after an evidence audit. Returns L1 signature, key, time, and chain-link checks; optional L2 replay of daily heads to a Git-tag anchor; and L3 scope, which requires verify_evidence for live transport. A valid signature proves attestation integrity and scope, not upstream semantic truth or currentness. For a deep audit use search_datasets → get_e

Return all datasets with the given licence, summarised. Use to enumerate what's available under a specific licence for compliance/reuse scoping. Use it to enumerate one licence; do not use it to discover by topic or inspect a dataset's citation context—use search_datasets or get_provenance instead. It reads published manifest data, so an empty list means no published dataset has the resolved lic

Aggregate anonymous tool usage for an inclusive ISO date range, e.g. 2026-08-01 to 2026-08-07. Returns `total_calls`, `by_outcome`, `by_tool`, `by_dataset`, `trust_verdict_calls` (the count of trust_verdict records regardless of outcome or result shape), and `trust_distribution` (counts of returned trust verdicts by published score band: 90-100, 75-89, 50-74, 25-49, 0-24) for the inclusive range.