SwarmWorld report verification
Type: agentic-system-analyses/types/agentic-system-verification.md
Verification
The supplied reports support a bounded implementation account. The previous containment blocker is repaired, and no material blocker remains. I read the complete invocation, supplied reports, types, contract, correction answers, structural check and previous verification. Only epistemic supplies a nonempty correction answer. The structural check reports none, so there is no structural failure to route. I independently inspected the frozen source rather than treating the answer or previous verifier's source checks as verification.
SRC-1 HEAD equals the revision in the boundary. Its top-level tracked entries agree with the boundary's coverage table; the runtime classification includes shipped drivers rather than excluding callers of the policy API. Source reads below supply implementation evidence, except the README and authoring skill, which supply doctrine/design. No target code, tests, examples or providers were executed. Source inspection establishes neither successful operation nor causal benefit.
Runtime, effects and workflow
I traced SRC-1, src/biofoundry/policies/llm.py, src/biofoundry/structured_output.py, src/biofoundry/providers/openai_compatible.py, src/biofoundry/cli.py and src/biofoundry/simulation.py through request construction, provider return, validation, research-state writing, queue commitment and world stepping. RT-RTE-model-planning and RT-RTE-world-stepping correctly distinguish representational admission from world-effect admission. The local validator uses its maximum rather than the provider's smaller configured plan limit. A transient provider error freezes a configured batch, restores scheduled memories and preserves queues; the CLI withholds stepping and retries. The convenience actions() path does not honor the commitment result. These are bounded driver protocols, not universal transaction or eventual-completion guarantees.
The objects and component retain supported identities: RT-OBJ-action-queues is pending typed action state; RT-OBJ-artifact-program hashes instructions rather than author/name/ancestry; RT-OBJ-scenario-prompt is static natural-language guidance; RT-CMP-configured-model leaves exact weights, endpoint mutability and provider-side updates unresolved. The provider's store=False request is not evidence of external retention compliance. These findings follow SRC-1, src/biofoundry/programs.py, src/biofoundry/scenarios.py, the policy and provider adapter.
I checked RT-RTE-direct-control against SRC-1, src/biofoundry/server.py, game/session.py, game/policy.py, src/biofoundry/env.py and src/biofoundry/policies/scripted.py. Manual/human actions override model plans; possession suppresses scheduling and queue consumption; environment and scripted controllers bypass model schema admission but reach simulator checks. The research-oracle is a separate privileged fixed-recipe controller, not an oracle consulted by the LLM. These alternatives bound claims about local model information and model autonomy.
For RT-RTE-program-install, I followed BUILD and WRITE/FORK through SRC-1, src/biofoundry/simulation.py, src/biofoundry/artifacts.py and src/biofoundry/programs.py. BUILD, defaults and explicit installation reach validation. Fork-specific known-parent, changed-content and acyclic-lineage checks do not govern every installation. The VM is straight-line and vocabulary/register bounded; repeated actuator instructions can accumulate independently clipped outputs. The report correctly avoids an aggregate 0.05 output guarantee, global numeric-safety guarantee, host sandbox or performance-based admission claim.
RT-RTE-scenario-admission agrees with SRC-1, src/biofoundry/scenarios.py and .agents/skills/swarmworld-world-builder/SKILL.md: safe YAML, contained paths, validation and hashing are implemented; author verification and non-mutation requirements are instructions, not automatically enforced production review. Cached definition loading and fresh validation differ. RT-BAP-model-guidance, RT-BAP-action-dispatch and RT-BAP-program-execution correctly separate interpretive model input, symbolic action admission and installed executable force. RT-CLM-grounded-science remains a request, not a truth guarantee.
The workflow account, including all three annotations, matches SRC-1, src/biofoundry/cli.py, the policy and simulator: software fan-out supplies agent-specific contexts; the driver honors commitment before consuming actions; action rejection and later feedback differ from successful scientific repair. Final recording and recorder closure precede summary return. Optional evaluation augments output; neither scientific success nor mandatory replay gates delivery. No new workflow records need identity reconciliation.
Retained evidence, selection and epistemic authority
SRC-1, src/biofoundry/memory.py and src/biofoundry/policies/llm.py support MEM-OBJ-agent-memory, MEM-OBJ-research-state, MEM-OBJ-retrieval-stats, MEM-RTE-context-selection and MEM-RTE-retrieval-feedback. Private deques are bounded; latest research state is delivered independently of ranked retrieval; availability filtering does not verify citations. Ranking and selection counters precede excerpting and packet omission. Trimming preserves stored originals, not necessarily delivered meaning, and the character budget can remain exceeded. The epistemic truncation example follows the inspected non-JSON branch without executing it. Its indeterminate semantic relation is justified; arbitrary truncation is not guaranteed non-ampliative reshaping.
I followed empirical writes, recipe/provenance admission, proposal evaluation and TEST through SRC-1, src/biofoundry/knowledge.py, src/biofoundry/simulation.py and src/biofoundry/science.py. MEM-OBJ-empirical-knowledge, MEM-OBJ-research-mission and MEM-RTE-evidence-retention preserve historical cell evidence, possession-based grounding and input/outcome retention. The corresponding EPI-OBJ-empirical-knowledge, EPI-OBJ-experimental-batch, EPI-RTE-sensor-evidence, EPI-RTE-batch-measurement, EPI-RTE-recipe-admission and EPI-RTE-proposal-evaluation correctly distinguish acquisition, arithmetic readout, eligibility and matched material ablation. Private test views and notebook records omit the target-threshold flag. Proposal-time utility is retained separately from the private validated-recipe text. These checks license simulator-domain findings, not real-material validity or acceptance of an explanatory theory.
Publication, teaching, requests and receipts in SRC-1, src/biofoundry/simulation.py, with archive operations in src/biofoundry/memory.py, support MEM-OBJ-cultural-archive, MEM-OBJ-deposited-insights, MEM-OBJ-message-records, MEM-RTE-social-retention, MEM-BAP-evidence-admission and EPI-RTE-insight-circulation. Public, spatial and private visibility differ. Recipient/fulfillment selection does not interpret request prose. Personally grounded resource mentions can grant combined-design eligibility without warranting publication assertions. EPI-OBJ-memory-record is a valid cross-store text container; intention strings are not automatically truth-apt claims.
SRC-1, src/biofoundry/program_library.py and the simulator's respawn path support MEM-OBJ-program-library, MEM-OBJ-program-skills and MEM-RTE-cultural-inheritance. Registry instructions, knowledge indices and installed execution differ. Verification flags can transfer; inheritance ranks verified entries by retained measurement-tail length, recency and ID, not demonstrated utility. Private/empirical memory resets independently of inherited skills.
SRC-1, src/biofoundry/events.py, src/biofoundry/counterfactuals.py, src/biofoundry/playback.py, src/biofoundry/cli.py and authoritative serialization in src/biofoundry/simulation.py support MEM-OBJ-event-trace, RT-RTE-recorded-replay and the memory replay annotation. Prompt factoring is reversible. Replay skips uncommitted research-state writes and steps recorded actions; compatibility, tick and digest checks bound agreement. It does not restore retrieval scoring/use evolution, and serialized memory omits selector statistics. Digest agreement is not complete adaptive-checkpoint equivalence.
RT-RTE-ecology-assay matches SRC-1, src/biofoundry/technology_ecology.py: copied frozen societies, optional disturbances and artifact knockouts provide conditional simulator comparisons; held-out generalization disables knockouts. The inspected episode records outputs rather than selecting a live successor. EPI-CLM-research-environment faithfully attributes SRC-1, README.md. The epistemic ledger and bounded conclusion preserve implementation versus operation, acquisition versus warranted derivation, checking versus disposition, and retention versus post-acceptance integration. No report declares an evidenced absence. The theory-builder, learning, reflection, autonomy and self-improvement findings remain independently scoped; no observed model output or actual benefit is inferred from their wiring.
Correction, relations and reconciliation
I independently checked the correction against SRC-1, src/biofoundry/cli.py, src/biofoundry/policies/llm.py, src/biofoundry/simulation.py and src/biofoundry/memory.py. EPI-RTE-memory-selection no longer asserts containment in planning. Its endpoints, immediate return, activation, adaptation-ledger qualification, coverage and bounded conclusion consistently separate planning-stage selection/use from subsequent executor outcome credit. That credit is written by _record_action_outcome after queue commitment and consumed by later retrieval. Its overlap with MEM-RTE-retrieval-feedback is explicit, not independent corroboration of another evaluator. The corrected answer holds; the previous blocker is discharged.
Every remaining declared Part of: relation is supported: context construction is within planning; social transfer, inheritance and the selected sensing/measurement/admission/evaluation/circulation subroutes are within world stepping. Cross-phase evidence retention and feedback appropriately lack single-parent containment. Reconciliation correctly supersedes the duplicate empirical cell/counter object and leaves valid containers, parts and differing consumer routes distinct. It disposes replay completeness, transferred verification and selected-versus-delivered issues without rewriting analyst values. The former feedback conflict is resolved in the current reports, not hidden as a limitation. No remaining unresolved cross-report disagreement was found.
Omission questions and stopping decision
I selected challenges from the frozen tracked tree, CLI dispatch and producer/consumer dependencies, not only cited quotations: whether direct controllers bypass model admission; whether BUILD bypasses executable validation; whether replay resumes every adaptive state; whether latent scores reach private agents; and whether offline selection contradicts the live no-assay-admission-feedback finding. The source traces above resolve the first four within the reports' stated scope. I also checked semantic-observation selectors, including configurable landmarks and public infrastructure; this supports bounded packet construction, not a universal claim that every controller or configuration has identical information.
For offline alternatives I inspected SRC-1, src/biofoundry/cli.py's independent-search aggregation and src/biofoundry/technology_atlas.py's embedding/cache implementation. Endpoint metric winners and retained semantic matrices are additional research-output mechanisms. They do not contradict the scoped live episode account, but they make system-complete automatic-selection and representation comparisons inappropriate. The reports explicitly reserve these offline internals; the remaining inventory limit is retained below. Further optional search stopped because the selected consequential challenges have supported dispositions and no identified material contradiction is left undisposed. Additional source could enrich the partial offline inventory, but unsearched behavior is not evidenced absence and is not needed to support the bounded positive runtime, memory and representative workflow findings.
Blockers
none
Limits
- The offline producer/consumer and evaluator inventory remains partial, as declared in the epistemic coverage account and memory integration issues. Additional verification reads of SRC-1,
src/biofoundry/cli.pyandsrc/biofoundry/technology_atlas.pyestablish endpoint-wise metric selection and embedding/cache mechanisms without reconstructing all statistical attribution, dense-representation provenance, visualization or generated-depiction consumers. Withhold system-complete evaluator, representation and automatic-selection comparisons. In particular, do not generalize RT-RTE-ecology-assay's live no-admission-feedback finding into absence of offline metric selection. The positive private/public/spatial/program memory routes and representative CLI workflow remain supported.