feat: inject historical reference into MAF - #8
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Add ExperienceFinalizationService: one call that loads a completed captured run, evaluates its own closed verification round, checks host authorization and the host's storage decision, reflects, creates the record as Candidate, and commits its initial lifecycle event to Validated or Quarantined. Record, reflection and event IDs derive from the run, so a retry re-derives them and converges instead of duplicating. Required checks can now name the evaluator kind that may satisfy them, and Core and Storage.Postgres each expose a service-registration extension. The MAF adapter finalizes a fully captured run through the host's resolver. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Add IExperienceCandidateSource with a PostgreSQL implementation: scope, status and confidence filtering plus a full-text match over a generated tsvector column added by migration 0003. Core's ExperienceRetrievalService applies expiry and environment eligibility, then ranks candidates on relevance, confidence, recency, status and environment compatibility with configurable validated weights, exposing every normalized component and effective weight. Retrieval is bounded by a timeout that returns an empty result with a timeout signal rather than throwing, caller cancellation stays distinct, and a capped candidate pool is reported through Truncated. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Add IExperienceEmbeddingIndex and a domain-typed embedding generator port, with a new AgentExperience.Storage.Postgres.Vectors package implementing them over plain Npgsql and Pgvector. Embeddings are derived data: indexing runs after the canonical commit, embeds only the sanitized retrieval summary of an eligible record, and writes conditionally on the record's exact revision, so a stale write is rejected and a deleted record is never recreated. Retrieval gains a vector channel merged with the text channel under the same eligibility, timeout and ceiling. A model or dimension mismatch, an unavailable provider, or a vector-channel failure produces an explicit flagged text-only result rather than an incompatible comparison. The vectors package owns and applies its own schema, so a text-only deployment never runs CREATE EXTENSION vector. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Add ExperienceContextProvider, a simple-tier AIContextProvider the host adds to ChatClientAgentOptions.AIContextProviders. It retrieves ranked experience before an invocation, re-checks every candidate against the same eligibility rules retrieval applies, asks the host's injection decision, and injects a delimited Historical Reference carrying source, confidence, applicability and an evidence summary -- never raw payload content, never a cut record. Limits drop whole records and record every omission. Retrieval that is empty, times out or fails leaves the agent running normally. Labeling marks the content untrusted; the authorization boundary is what denies an unauthorized tool call, and a test proves it does when the model obeys injected text. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
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Summary
Story 2.3, and the last of Epic 2. The loop closes: a run is captured, verified, reflected on, finalized, indexed — and a later agent receives it.
ExperienceContextProvideris a simple-tierAIContextProvider(Story 1.7 rejectedTextSearchProvider: no confidence or applicability fields, and no timeout). The host adds it toChatClientAgentOptions.AIContextProviders; the capture extension never builds those options, so injection is deliberately a separate type.Per invocation it resolves a retrieval request, retrieves, selects within the record limit, re-checks every candidate against the same eligibility rules retrieval applies — status, confidence floor, expiry and required environment attributes — asks the host's
InjectionDecision, then writes one delimited block.On labeling
Labeling is hygiene, not a control, and the docs say so. The test that matters makes the model obey the injected instruction and emit a guarded tool call:
ApprovalRequiredAIFunctionmeans the tool body never runs. It asserts the boundary held, not that the model behaved.Known limitation, now documented and pinned by a test
Injected blocks accumulate in a session's history: turn 2 carries the fresh block and turn 1's copy. So a record revoked between turns keeps being sent from the earlier block, and the byte budget bounds one invocation rather than a conversation. MAF filters a provider's input to external messages, so the provider cannot reliably detect its own earlier blocks. Use a fresh session per task when that matters.
Review
Three reviewers raised 35 findings; 34 fixed, 1 deferred (a batched by-IDs read for the re-check). The serious ones: the final check was narrower than the eligibility it claimed to re-apply; the session accumulation above; and nothing pinned the injected message's role, so a switch from
UsertoSystemwould have inverted the posture with every test green.Test plan
dotnet build --configuration Release: 0 warnings, 0 errorsdotnet test --configuration Release: 680 of 680 pass (MAF 86, Core 382, Postgres 125, Vectors 43). Locally withTESTCONTAINERS_RYUK_DISABLED=true.ChatClientAgent, plus the authorization test, a three-turn session test, cancellation, and a loop-closure test that captures and finalizes a run then receives its own lesson back.🤖 Generated with Claude Code