Citadel report verification
Type: agentic-system-analyses/types/agentic-system-verification.md
Verification
I read the complete pinned boundary, runtime, memory, epistemic, workflow and reconciliation members, the correction answers, structural check and previous verification. The structural check reports none; no structural failure requires routing. Memory supplies one corrected answer; the other answer files are empty. I judged the current records against source rather than treating the previous verdict or correction answer as proof. Checkout HEAD equals the revision in the Source register, and the tracked root inventory remains consistent with the whole-system memory-system boundary. All source inspection below is implementation or doctrine/design evidence under SRC-1, not target execution. No target tests, examples, providers or services were run.
Correction and identity review
The previous blocker is resolved. MEM-RTE-source-enrichment no longer declares containment under the HTTP RT-RTE-ingest-admission. Its route description, admission account and integration issue now distinguish direct learning from HTTP admission. I independently traced ingest into execute_learning_writes, its default and forwarded allow_llm=False, and the disabling branch in LearningProcess.learn; direct learning instead defaults to True, subject to tier and enrichment configuration. SRC-1: kb/server.py, kb/learning.py. Enabled enrichment is therefore not attributed to the HTTP route. The correction preserves the supported optional mechanism rather than withdrawing it.
I checked every declared record, annotation and source anchor for identity, evidential scope and support, including the distinction between wired implementation and uninspected operation. No evidenced-absence record is declared. The two amendments in reconciliation identify genuine duplicates: EPI-OBJ-node-note and MEM-OBJ-node-note name the same extracted artifact; EPI-RTE-source-enrichment and the memory enrichment route now name the same optional direct-learning transformation. Supersession preserves the epistemic findings rather than replacing them with stronger memory findings. EPI-OBJ-enriched-chunk is an output, not another route. The remaining formal parts are supported: EPI-RTE-note-distill is the extraction part of automatic capture; EPI-RTE-automation-receipt is a prerequisite part of scheduled curation. SRC-1: kb/session_trace_distill.py, kb/learning.py, kb/llm_enrichment.py, kb/self_improve.py, kb/improvement_policy.py.
Runtime, retention and read-back
HTTP role/scope checks, seat write routing, privileged allowlist bypass and direct local CLI calls support the bounded protocol account, not universal isolation or remote escalation. I checked the alternate principals and omitted-dataset search expansion, not just the guarded seat branch. RT-RTE-local-access correctly gives the local operator a different envelope. RT-CLM-explicit-approval is tool policy: the MCP request has no consent attestation, and automatic capture and promotion are countercases to universal human approval. SRC-1: kb/server.py, kb/cli.py, kb/mcp_server.py.
Service admission, source retention and worker projection support RT-OBJ-ingest-result, MEM-OBJ-source-revisions, MEM-OBJ-projection-receipts and RT-RTE-source-projection. Acceptance is not completed indexing. Deferred HTTP capture can still start vector-only work; the reports do not incorrectly extend generative-enrichment suppression to embeddings or all later computation. Worker relational visibility, vector chunk and graph presence checks are backend-domain checks, not factual validation. SRC-1: kb/service.py, kb/lifecycle.py, kb/lifecycle_worker.py.
I followed service search through exact Linear identity lookup, scoped vector recall, lifecycle binding, lexical merging and the final GitHub-state fallback. MEM-BAP-current-head and EPI-RTE-source-withdrawal retain path-specific eligibility, not universal erasure. Historical revision lookup in MEM-RTE-document-drilldown is compatible with current-search exclusion. Canonical document shaping removes redundant aliases rather than imposing the hit-text budget. SRC-1: kb/service.py, kb/lifecycle.py, kb/search_format.py.
Hook query cleaning, redaction, top-three rendering and caps support RT-RTE-task-search and RT-BAP-context-delivery. The memory annotation correctly distinguishes automatic task-triggered supply from explicit MCP/CLI calls and their configurable text budget. These are bounded deliveries, not demonstrated host compliance, conversation compaction or subagent contexts. SRC-1: kb/hooks/search_inject.py, kb/search_format.py.
Transformation and warrant
Automatic RT-RTE-session-capture and volunteered MEM-RTE-share-session have different selection, transport and admission. I checked transcript allowlisting, deterministic extraction, byte cap, forced author identity, dual writes and failed-target retry. MEM-OBJ-session-trace is distinct from the personal note. The failed-tool countercase in the epistemic note route is supported by reachable dictionary/block processing: node-note file paths come from tool-use inputs without checking tool-result success, and last assistant text becomes Outcome. It remains a deduction, not a supplied execution. SRC-1: kb/hooks/sync_session.py, kb/session_trace_distill.py, kb/server.py.
Enrichment shape checks do not enforce EPI-CLM-preserve-source. Optimization similarly uses selected labels/tags and known-label parsing rather than full-source semantic verification. RT-OBJ-optimize-prompt, RT-RTE-index-curation, RT-BAP-curation-guidance and MEM-OBJ-optimization-note correctly separate requested model behavior, additive note admission, original-source editing and opaque provider improve. Dry-run suppresses note application, not the preceding improve call. Indeterminate generated-content relations are justified; missing entailment proof alone does not establish ampliative conjecture. SRC-1: kb/llm_enrichment.py, kb/self_improve.py, kb/cognee_client.py.
The four runtime model components retain separate parameter-update, pinning and endpoint-substitution assessments. Mutable aliases and configured profiles do not establish immutable weights; projection writes do not establish weight training. RT-RTE-skill-refresh detects deployment-file hash changes rather than authoring new skills. SRC-1: kb/llm_enrichment.py, kb/promotion.py, kb/model_routing.py, kb/embedding_profile.py, kb/skills.py.
MEM-OBJ-feedback-events, MEM-RTE-feedback-processing and EPI-RTE-feedback-record distinguish metadata classification, QA-cache handling, searchable fallback and optional gated improvement. A ranking-evaluation candidate does not install a ranker. MEM-OBJ-obsidian-revisions and MEM-RTE-vault-sync correctly retain JSON save before separate size/scan/search admission. This qualifies store scope without contradicting HTTP ingest rejection. SRC-1: kb/service.py, kb/feedback_store.py, kb/server.py, kb/obsidian_sync.py.
Digest formatting and notification predicates support EPI-OBJ-organization-digest and EPI-RTE-digest-build, not accepted factual knowledge. Conflict hashing/status resolution, lexical verify shaping and legacy cleanup support EPI-OBJ-conflict-record, EPI-RTE-conflict-record, EPI-RTE-verify-report and EPI-RTE-garbage-cleanup within their stated domains, not semantic adjudication. SRC-1: kb/organization_digest.py, kb/learning_agent.py, kb/conflicts.py, kb/agent_workflows.py, kb/service.py.
I checked answer-span scoring separately from expected-document matching and comparison enforcement. MEM-CLM-retrieval-evaluation, EPI-OBJ-benchmark-run and EPI-RTE-benchmark-gate preserve the oracle and command-exit domain. EPI-CLM-benchmark-score remains attributed reporting, not a supplied authenticated run. EPI-OBJ-evaluation-gate describes another object: timestamped Boolean assertions licensing automation, not replayed measurements. Public context-link and promotion claims remain bounded by EPI-CLM-context-links and EPI-CLM-promotion-gate. SRC-1: kb/retrieval_eval.py, kb/improvement_policy.py, README.md.
Workflow and omission disposition
The selected workflow is source-connected rather than assembled from unrelated capabilities. I traced scheduled seat iteration and receipt prerequisite, bounded enumeration, reference heuristics, typed-decision/chat fallback, threshold and rejection checks, automatic versus queued writes, candidate-body removal at review listing, admin decisions, full-candidate reload and Central acceptance accounting. Failed approvals consume the pending item; browser HTTP success does not inspect promoted. These support RT-RTE-promotion-review without asserting successful execution or guaranteed retry. SRC-1: scripts/run_railway.py, kb/promotion.py, kb/promotion_refs.py, kb/server.py, web/src/pages/app/review.tsx, web/src/lib/api.ts.
I reviewed every reconciliation integration disposition. Rejection versus retention, withdrawal versus historical expansion, and deterministic extraction versus unverified outcome labels are compatible scope distinctions, not unresolved contradictions. Feedback retention is a valid focused account alongside broader event processing; neither supersedes the other's whole referent. No unresolved conflict or missing material split requires a reconciliation blocker.
Consequential omission questions came from the frozen tree, alternate shipped callers and producer/consumer dependencies: could another admission route defeat approval or model-exclusion claims; could another return branch defeat withdrawal claims; could a downstream client or evaluator provide stronger acceptance or delivery? Direct learning, local access, automatic capture, shared traces, Obsidian ordering, all service search return branches, historical drilldown, scheduled promotion/feedback and the review API helper supplied dispositions above. Additional SRC-1 inspection of kb/capture.py found bounded README/commit-summary payload construction through ingest, not a local generative loop; kb/agent_workflows.py also exposes prepare-PR-context shaping, which does not turn verify pointers into factual acceptance. This adds implementation coverage, not observed operation. Further optional expansion stopped because no identified material challenge lacks a disposition and current findings do not assert exhaustive coverage. Remaining partially traced mechanisms limit inventories and stronger guarantees without invalidating the retained account.
Blockers
none
Limits
- MEM-OBJ-search-projections, RT-RTE-index-curation and EPI-RTE-automation-receipt leave the upstream Cognee improvement successor and its later consumer opaque, and establish receipt assertions rather than issuer measurements. The explicit optimization-note write remains supported. Withhold complete maintenance-transformation, accepted-knowledge and improvement comparisons for the opaque alternative.
- MEM-RTE-vault-sync, MEM-RTE-document-drilldown, EPI-RTE-source-withdrawal and the memory report's coverage table leave connector checkpoints, backup/restore, some repair/capture branches and detailed plugin application incompletely traced. Retention, selected retrieval and inspected ordering remain supported; withhold complete corpus, universal erasure, cross-store rollback and exhaustive route-inventory comparisons.