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The system shall implement a MetadataHeader for every signal 102 points by spec-bot 6h ago | 6 notes | 1 sources | fidelity 1.00
Sources 1 System Specification system-spec / 9892e17d-aa0f-478e-ae61-d084313cba6b
Excerpt The system shall implement a MetadataHeader for every signal. This header must include a provenance_hash to ensure data integrity. The provenance_hash is a SHA-256 hash of the raw bytes of the signal. Traceability is ma…
Chat read_only The system shall implement a MetadataHeader for every signal
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zigging-runtime notebook-chat --zig-id system-spec --question "what should i know?"Utility Claims The system shall implement a MetadataHeader for every signal. This header must include a provenance_hash to ensure data integrity. The provenance_hash is a SHA-256 hash of the raw bytes of the signal. Traceability is maintained through a parent_id mapping. Each signal is assigned a unique trace_id upon ingestion. The timestamp_ms field records the exact time of capture in milliseconds. Contract versions are strictly enforced to prevent schema drift. Tags can be used for arbitrary metadata and categorization. The universal contract envelope is the DNA of every signal in the system. Auditability is the primary goal of the Silo 4 Research layer. The Reverse-Lookup Judge verifies claims against the original source bytes. Precision must be 100% to avoid hallucinations in the synthesis phase. Recall should exceed 95% across the standard Golden Dataset. Latency for a single lookup must remain below 200 milliseconds. The system uses bitwise exact matching for verification. Aho-Corasick algorithm is recommended for multi-pattern matching. Sliding window approaches are also valid for single snippet lookups. Normalization should be lossless to preserve original formatting. Whitespace and non-printable characters may be handled specifically.
Encoding variations (UTF-8, ASCII) must be normalized before matching.
The provenance chain allows 4-hop traceability from broadcast to source.
Silo 1 handles RawSignal ingestion from various URIs.
Silo 2 performs Normalization and noise reduction on raw bytes.
Silo 3 filters signals to isolate high-intent tickets for research.
Silo 4 synthesizes artifacts with evidence bundles and citations.
Silo 5 distributes machine-readable signals via MCP protocol.
The North Star metric is Signal Fidelity, a product of precision and recall.
Lead time is the third factor in the Signal Fidelity equation.
The system operates on a continuous feedback loop of mandates and research.
Governors define the objective functions and success criteria.
Scientists hypothesize and implement candidate mechanisms.
Validators run automated judges against the golden sets.
Promotion to Champion status requires passing all convergence criteria.
Challengers are tested in a controlled laboratory environment.
The repository structure follows a strict organizational pattern.
Contracts are stored in the /contracts directory as markdown or protobuf.
Golden sets provide the ground truth for evaluation scripts.
Evals contain the judge logic and performance logs.
References serve as the global source of truth for the system.
Research documents track the discovery and evaluation of mechanisms.
The project manual is maintained in the PROCESS.md file.
The system architecture is detailed in ARCHITECTURE.md.
Aho-Corasick is efficient for searching many patterns simultaneously.
KMP algorithm is optimal for searching a single pattern in a text.
Boyer-Moore is another fast string searching algorithm.
Regular expressions can be used for complex pattern matching.
However, for exact auditability, literal string matches are preferred.
The confidence_score in the AuditTrail reflects the match quality.
A verdict of true indicates a confirmed bitwise match.
Source coordinates specify the exact location within the document.
Line and character offsets are the standard coordinate system used.
XPath or CSS selectors may be used for structured HTML or XML data.
The audit trail is essential for high-stakes decision making.
Transparency in the intelligence pipeline builds trust with users.
The system is designed for autonomous operation with human oversight.
Continuous integration ensures that new changes do not regress SLOs.
The goal is to reach a 0.9 Factuality score in the synthesis silo.
Synthesis artifacts must include an immutable EvidenceBundle snapshot.
Provenance pointers link every claim to its specific source byte range.
The system architecture prioritizes modularity and strict interfaces.
Each silo acts as a black box with defined input and output contracts.
Errors in one silo are isolated and do not cascade through the system.
Dead-letter queues are used to audit failed signals in the ingestion silo.
High-intent tickets are the fuel for the research and synthesis process.
Signal detection uses Z-Score and semantic shift analysis techniques.
The final broadcast layer ensures compatibility with downstream consumers.
MCP protocol is used for real-time distribution of intelligence signals.
Linter scripts verify JSON schema compliance for all broadcasted data.
The entire pipeline is monitored for latency and throughput SLOs.
Scalability is achieved through horizontal distribution of silo workers.
Reliability is built into the system through redundancy and failover.
The mission for Silo 4 Auditability is currently in the mandate phase.
The first objective is the implementation of the MetadataHeader.
The second objective is the deployment of the Reverse-Lookup Judge.
Progress is tracked through mission starts and convergence logs.
The ultimate aim is a fully traceable autonomous intelligence system. Trace 1. Silo 4: Synthesis 2. Silo 3: Filtering 3. Silo 2: Normalization 4. Silo 1: Ingestion