Interview Doc Agent synthesis verification
Type: agentic-system-analyses/types/agentic-system-verification.md
Verification
I checked every substantive statement in the public synthesis against the handed boundary, runtime, memory, epistemic and workflow members, applying the reconciliation's four object supersessions. The synthesis cites the surviving materials, JD and output records and does not rely on a superseded object for a stronger finding. I also checked carriage of the report and profile verifications' limits. No source reads, new evidence or corrected text were introduced.
The opening supplies a self-contained evidence boundary: the complete shipped instruction-and-document artifact, not its external execution hosts. The Source register supports doctrine/design evidence only. The synthesis consistently distinguishes requested behavior from inspected machinery, successful execution and benefit. Its host ownership, initialization and direct model admission account agrees with RT-CMP-host-ai, RT-RTE-initialize-workspace and RT-RTE-consolidate-experience.
The raw-to-dossier-to-index-to-later-request progression preserves the factual, locator and style roles of retained text. Project why/how content is not treated as extraction provenance. Selection remains model-directed reading, not context isolation or guaranteed recall. Raw-detail fallback and the whole-library alternative qualify the primary-source interpretation. The supporting records are MEM-OBJ-experience-dossiers, MEM-OBJ-personal-profile, MEM-OBJ-wiki-index, RT-RTE-generate-document and MEM-CLM-retrieval-reliability.
The numerical policy, fictional-example warning and absence of independent acceptance are faithfully separated. The synthesis does not promote retention to warrant, or missing entailment evidence to established conjecture. Its bounded checking negative agrees with EPI-ABS-content-check; its cross-output qualification agrees with RT-CLM-numeric-fidelity and EPI-CLM-source-consistency. The workflow account supports separate user triggers, local output placement and optional refinement. RT-RTE-feishu-writeback supports permission-dependent manual persistence, not factual review or uniform cloud delivery.
The final assessment leads with supported retained-content reuse and request-triggered revision. It does not infer improved future capacity, theory criticism, reflection or self-improvement from those contributions. The runtime supplies no separate theory-builder condition assessments, so withholding findings on conditions 1–4 does not strengthen it. Trace-origin uncertainty remains distinct from bounded local protocol absences in MEM-ABS-memory-maintenance. The proposed resolving evidence is appropriate to execution, fidelity, retrieval and method-improvement questions; no product ranking or transfer advice is added.
The limitations table preserves both settled verification limits and their prevented conclusions. It also carries operational, provenance, context, cloud, maintenance and provider-transmission uncertainty beside the relevant records. The reconciliation reports no unresolved conflict. No additional material defect was found; structural acceptance alone was not treated as evidential support.
Blockers
none
Limits
- RT-RTE-initialize-workspace and RT-RTE-generate-document: SRC-1,
SKILL.md,docs/02-安装-obsidian.mdand the starter-file names leave workspace resolution and default-template discovery unresolved. The first row of synthesis limitations faithfully carries this settled limit. Readers may retain the declared maintenance/read-back loop but should withhold guaranteed out-of-the-box discovery, resolved template fallback and uniform cross-host setup. - MEM-ABS-memory-maintenance, RT-RTE-initialize-workspace and MEM-OBJ-output support bounded local trace-learning negatives, while MEM-OBJ-materials, RT-RTE-consolidate-experience and RT-RTE-feishu-writeback leave dossier origin and cloud alternatives unresolved. SRC-1,
materials/README.md,SKILL.mdanddocs/03-接入-飞书.mdsupply the relevant declared mechanisms. The trace-learning row of synthesis limitations faithfully carries the settled overcautious aggregate-label issue. Consumers should preserve the classified local negatives but withhold a system-wide trace-learning negative and any interpretation of the aggregate uncertainty as erasing those local findings.