EvoOntology report verification

Type: agentic-system-analyses/types/agentic-system-verification.md

Verification

The reports support publication of a bounded account with the InsightBench inventory limit below. The DDR correction is supported. The supplied structural report check is none; there is no structural failure to route. I judged the current reports, their correction answers and reconciliation afresh. Neither the previous verification nor an author's validation statement substitutes for source support.

Boundary and source checks

I rechecked SRC-1 HEAD against the frozen revision, found clean Git status, and compared the top-level tracked tree with boundary coverage. I directly traced the root MCP dispatcher, operations, models, store, semantic runtime, validator, workflow, trajectory, trigger, session and aggregation implementations. I also read Codex host instructions and Build/Evolve skills, the evolution data-boundary reference, both POSIX launchers, the Claude reminder and hook registration, benchmark registry, all three adapters, and selected benchmark producer/consumer ranges identified below. A read-only comparison found the 25 root Python core files identical to their corresponding files in both plugin bundles; this does not establish prompt parity.

These checks preserve the knowledge-layer classification and inclusion of shipped benchmark callers. No source contradicts the frozen boundary kind. Implementation and instructions establish capabilities and policy, not observed grounding, host compliance, independent evaluation, successful execution or causal benefit. No target code, tests, examples, providers or benchmark runs were executed.

Runtime records and guarantees

I checked every runtime declaration against its source-supported role and evidence strength. RT-CMP-host-model, RT-CMP-bird-provider, RT-CMP-ddr-provider, RT-CMP-tool-calling-chat and RT-CMP-llm-judge distinguish separate model dependencies. Configurable inference aliases/endpoints do not establish immutable weights; inaccessible provider internals remain uninspected. The core aggregates judge verdicts without calling the judge. Source basis: SRC-1, plugins/evoontology-codex/AGENTS.md, benchmarks/bird/agent/llm_providers.py, benchmarks/ddr_10k/agent/llm_providers.py, benchmarks/insightbench/insightbench/tceo/tool_chat.py, evoontology/evaluation/evaluation.py.

RT-RTE-build-publication, RT-RTE-semantic-retrieval and RT-RTE-task-execution match the inspected handoffs. Host semantic judgments differ from structural publication checks. Semantic calls reload and deliver selected guidance. Task start pins a mutable version name; resolution records a potentially truncated event; completion requires a non-error native event, not a verified answer. Built-in SQLite obtains observations directly under local read-only/action/progress/row limits. Manually supplied events depend on caller integrity. Source basis: SRC-1, evoontology/runtime/mcp_server.py, evoontology/runtime/runtime.py, evoontology/runtime/ops.py, evoontology/workflow.py, evoontology/validate.py.

RT-OBJ-evolution-session, RT-RTE-evolution-admission and RT-RTE-version-override correctly separate lifecycle admission from administrative alternatives. Acceptance validates the candidate and recomputes a current-round/current-candidate gate over supplied inputs. Publication/selection precedes checkpoint advancement and accepted-run saving. Direct save/select/promote paths bypass that gate; named content remains mutable. Thus neither trustworthy all-path improvement nor a crash-safe multi-file transaction is established. Hypothesis persistence is wired, while content-dependent criticism, iteration and autonomous diagnosis are instruction-level assessments. The dormant self-change pathway is not upgraded to exercised or successful self-improvement. Source basis: SRC-1, evoontology/evolution/session.py, evoontology/ontology/store.py, plugins/evoontology-codex/skills/evolve-ontology/SKILL.md.

RT-RTE-benchmark-evaluation and RT-RTE-benchmark-tool-loop accurately describe the selected subprocess and model/tool routes. All three adapters omit formal gate_input; DDR can evaluate existing logs and BIRD selects the newest matching results file. BIRD's bounded retries, first-tool dispatch and final no-tools SQL request are supported. BIRD/DDR history translation differs from InsightBench's fresh per-call frame. InsightBench blocks Python call five and later but executes earlier code in-process, not in an OS sandbox. These findings survive its fallback alternative, subject to the limit below. Source basis: SRC-1, benchmarks/bird/evolution_adapter.py, benchmarks/ddr_10k/evolution_adapter.py, benchmarks/insightbench/evolution_adapter.py, benchmarks/bird/agent/data_agent.py, benchmarks/ddr_10k/agent/data_agent.py, benchmarks/insightbench/insightbench/tceo/tool_chat.py, benchmarks/insightbench/insightbench/utils/agent_utils.py.

RT-CLM-evolution-success, RT-BAP-skill-guidance, RT-BAP-semantic-guidance and RT-BAP-session-gate retain the distinction between objective, interpretive policy/guidance and API-local enforcing veto. Their retained passages support these assessments without establishing activation or benefit.

Memory records and corrected delivery

I checked MEM-OBJ-term, MEM-OBJ-mapping, MEM-OBJ-relation, MEM-OBJ-constraint and MEM-OBJ-evidence through loading and actual root delivery. Mixed symbolic/text consumption, omitted mapping qualification fields, term-target constraint selection and deduplicated evidence bodies are supported. Evidence strings are assertions, not authenticated receipts; block severity is interpretive here. Source basis: SRC-1, evoontology/ontology/models.py, evoontology/runtime/runtime.py, evoontology/validate.py.

MEM-OBJ-trajectory, MEM-RTE-trace-retention, MEM-OBJ-workload and MEM-RTE-workload-reuse correctly distinguish lossy normalization, retained question/provenance selection and model-directed semantic editing. Project events retain order; benchmark semantic/native lists do not preserve a single cross-family order. BIRD recording rereads active_version even when evaluation selected another version. InsightBench's normalized record has semantic IDs/status and no native calls. All user questions survive workload selection, so its limit is not a universal count ceiling. Source basis: SRC-1, evoontology/trajectory/trajectory.py, evoontology/workflow.py, benchmarks/bird/trajectory_recorder.py, benchmarks/bird/run_evaluation.py, benchmarks/ddr_10k/agent/data_agent.py, benchmarks/insightbench/insightbench/runner.py.

The three Part of: relations are supported: MEM-OBJ-hypothesis, MEM-OBJ-evaluation and MEM-OBJ-source-references identify distinct explanation, gate-summary and pointer payloads within the runtime session container. MEM-OBJ-checkpoint and MEM-RTE-reminder-delivery identify separate workspace metadata and reminder supply. Latest-trajectory advancement does not enforce frozen-batch membership; stored source pointers do not authenticate or load their targets. MEM-OBJ-version-report and MEM-RTE-explorer-projection match annotation copying, all-version embedding and terminal aggregate display. Presentation is not another acceptance decision. Source basis: SRC-1, evoontology/evolution/session.py, evoontology/trigger/trigger.py, plugins/claude-code/scripts/check-reminder.py, evoontology/workflow.py, evoontology/visualization/renderer.py, evoontology/runtime/ops.py.

I independently rechecked MEM-RTE-ddr-guidance, its correction answer, and dependent Core ideas, Read-back and Integration issues. SRC-1, benchmarks/ddr_10k/tceo/runtime.py, invokes task filtering only when task is supplied. Startup and session regeneration in benchmarks/ddr_10k/agent/data_agent.py, and the resource caller in benchmarks/ddr_10k/tool_server/semantic_mcp.py, omit it. A scoped search of DDR Python manifest calls found no shipped invocation supplying task. The revised report correctly distinguishes optional targeting/capping from shipped unfiltered financial-reference delivery. The earlier blocker is resolved, not merely caveated.

MEM-RTE-bird-guidance and MEM-RTE-insight-guidance preserve local consumer differences: BIRD drops lifecycle metadata and follows term evidence bodies only; InsightBench replaces browse-history sets, has an uncapped Python mention loop and empty-resolve binding fallback, and does not send evidence bodies. DDR does not deliver the promised sample_query. Root item caps and withdrawal rules therefore cannot be generalized. I also checked all memory annotations against their supplied referents; none changes their identity. Source basis: SRC-1, benchmarks/bird/tceo/loader.py, benchmarks/bird/tceo/runtime.py, benchmarks/ddr_10k/tceo/runtime.py, benchmarks/insightbench/insightbench/tceo/retriever.py, benchmarks/insightbench/insightbench/tceo/session_manifest.py.

Epistemic, workflow and reconciliation

I checked every epistemic declaration and ledger function against the traced source behavior. EPI-OBJ-term, EPI-OBJ-mapping, EPI-OBJ-relation, EPI-OBJ-constraint and EPI-OBJ-evidence identify the same five root families as memory. Potential truth-apt content is not observed accepted knowledge. EPI-RTE-version-validation checks selected structure/references/loadability, not semantic truth. The concrete mapping-evidence precedence and projection account in EPI-RTE-semantic-projection is supported; its containment within root retrieval is substantive.

EPI-RTE-gate-aggregation and EPI-RTE-sql-comparison are check parts of admission and benchmark evaluation, respectively. Arithmetic/counting and sorted-row comparison warrant conditional conclusions over inputs, not their authenticity or causal explanations. EPI-CLM-grounded-commitment and EPI-CLM-gated-versioning accurately preserve stronger design requirements alongside weaker enforcement. Instruction-level semantic generation, acceptance and post-acceptance integration are not contradicted by wired serialization/publication. Unassessed downstream DDR/InsightBench metrics prevent a complete semantic-checking negative; none is emitted. No analyst declares an evidenced absence. Source basis: SRC-1, README.md, plugins/evoontology-codex/skills/build-ontology/SKILL.md, plugins/evoontology-codex/skills/evolve-ontology/SKILL.md, evoontology/ontology/models.py, evoontology/runtime/runtime.py, evoontology/validate.py, evoontology/evaluation/evaluation.py, evoontology/evolution/session.py, benchmarks/bird/run_evaluation.py.

The selected workflow account and its annotation match Codex authorization, frozen handoffs, host diagnosis, evaluation orchestration, rejection continuation, reason-specific incomplete guards, terminal finalization and separate presentation failure. Reporting and panel opening remain host responsibilities. There is no manufactured internal delegation or claimed successful execution. Source basis: SRC-1, plugins/evoontology-codex/skills/evolve-ontology/SKILL.md, evoontology/evolution/session.py, evoontology/runtime/ops.py.

I checked every amendment, containment connection and integration disposition in reconciliation. The five supersessions establish family identity without replacing epistemic values. The three memory object parts and three epistemic route parts leave valid containers intact. Narrow transformations and consumer-specific routes are not duplicate enclosing loops. Initial grounding, publication conditions and search-completion objectives have different scopes. The DDR correction creates no current cross-report disagreement. Version lineage, trace loss, checkpoint scope and misleading source labels are supported refinements rather than conflicting analyst claims.

The reconciliation's missing-part conflict is disposed as the local inventory limit below. Direct source inspection confirms fallback and retained analytical history. Neither report asserts their absence or claims a complete InsightBench recovery/history inventory; memory explicitly names the omitted mechanisms. They do not alter the central ontology persistence/admission conclusions or the selected Codex workflow. Consequently the partial inventory can remain faithful without requiring new declarations before publication. This disposition does not equate checkpoint history with normalized trajectories or promote carried findings to observed operation. No other unresolved disagreement needs a blocker.

Omission questions and stopping decision

The consequential questions were selected from the frozen tree and producer/consumer dependencies: whether alternate state writes evade admission; whether local readers preserve lifecycle withdrawal and evidence; whether shipped manifests actually use task targeting; and whether InsightBench has alternate execution or retained-answer consumers outside the selected tool loop. Root store/handler tracing, local retrieval reads, the DDR caller search, and InsightBench answer/checkpoint/history inspection disposed these questions. Gate bypass and consumer variation are already retained; DDR wording is repaired; InsightBench remains a local partial-inventory limit.

Further optional expansion stopped because no identified material challenge remains without a disposition. Detailed binder accuracy, downstream evaluator semantics, external host compliance and actual causal benefit remain unestablished beside the affected claims. Available but uninspected code is not absence. More exhaustive inventories would not be needed to support the emitted bounded findings; no universal truth, sandbox, targeting, trace completeness or successful-improvement claim depends on them.

Blockers

none

Limits

• RT-RTE-benchmark-tool-loop, MEM-RTE-insight-guidance, MEM-RTE-trace-retention and MEM-OBJ-trajectory remain a selective InsightBench execution/retention inventory. The missing-part conflict in reconciliation concerns additional fallback and checkpoint-history mechanisms, not contradictory presence/absence claims. SRC-1, benchmarks/insightbench/insightbench/agents.py, catches RuntimeError from tool-calling code generation and invokes baseline generate_code with semantic_manifest=None. That does not prove absence of semantic influence: the schema can already have been enriched. The same file persists insights_history and semantic trace metadata, exposes checkpoint loading, and consumes analytical history in question selection/follow-up or summarization. These payloads differ from normalized trajectories. Withhold comparisons assuming all execution uses ToolCallingChat, fallback preserves semantic-tool access, or normalized trajectories exhaust retained analytical history. The ontology route, local context-frame findings and selected Codex workflow remain supported. Source wiring does not establish successful fallback or exercised checkpoint reuse. Minimum supporting passages are:

except RuntimeError as e: --- benchmarks/insightbench/insightbench/agents.py

solution = au.generate_code( --- benchmarks/insightbench/insightbench/agents.py

self.insights_history = payload.get("insights_history", []) self.semantic_events.clear() self.semantic_events.extend(payload.get("semantic_events", [])) --- benchmarks/insightbench/insightbench/agents.py