memory_calibrate

shallow

io.github.AzielEliab/aziel-runtime · Verify this server

Calibrate one memory with the deterministic 3-of-4 triad plus Bayesian posterior (AKM-TRIAD-1.0). Writes a LEARN stamp — not a ranked search and not an explain view. Use this when an observed memory should receive a posterior after evidence, not a ranked search. Do not use it for observing a new fact, resolving an outcome, or explaining a stored node; use memory_observe, memory_resolve, or memory_get instead. Write: forward-only RoseClock LEARN stamp. Posterior ≠ truth. authorizes_action=false. No automatic MODEL_UPDATE. subject or memory_id recommended. use_case labels calibration; it is not a permission. Mutation requires confirm=true (runtime gate) or dry_run=true (preview only, no write). confirm and dry_run stay optional on inputSchema.required. dry_run still returns FG-HALLUC-TOOL, FG-STUB, FG-UNKNOWN-OP, or FG-LOCAL-ONLY when a confirm call would refuse. confirm is consent, not tenant auth, and it does not upgrade shared public-demo isolation. Returns triad_score, omitted leg, posterior, effective N, and Brier notes.

100.0/100

1 trials · measured 1 day ago

memory_calibrate scores 100.0/100 on Vouch's measured behaviour index, from 1 real invocation trials against io.github.AzielEliab/aziel-runtime, measured 6 Oct 2026 under methodology v0.2.0. Every measured component scored 100.

Component breakdown

ComponentWeightValue
Reliability35%not applicable
Schema integrity25%100.0
Failure behaviour15%not applicable
Latency15%not applicable
Concurrency10%not applicable

Tool details

Transport
remote
Credential class
self-provisionable
Input schema
not declared
Output schema
not declared
Side-effect classification
unclassified

Score history

DayScoreTierMethodology
2026-10-06100.0shallowv0.2.0

Probe evidence

ProbeOutcomes
schema_integritypass: 1

Raw request/response logs are not archived yet — the outcome counts above are drawn directly from every recorded trial.

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Vouch score: memory_calibrate
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memory_calibrate — Vouch