131 lines
6.1 KiB
Markdown
131 lines
6.1 KiB
Markdown
# Future Work
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Current Notarius behavior is documented in the canonical README, CLI,
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configuration, operations, internal, and integration docs. This roadmap records
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future work only. Items are ordered roughly by current value and specificity,
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not as committed release dates.
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## Near-Term D&D Pipeline
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### Evaluate Spell Extraction And Normalization
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- Evaluate ordinary extraction retries and the completed normalization path
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against a human-reviewed transcript set before adding repair-aware retries or
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an LLM-backed semantic validator.
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- Maintain a small set of human-reviewed transcripts and outputs for prompt,
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validator, and normalizer development. Treat model-quality review as an
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iterative human evaluation aid, not a deterministic correctness gate.
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### Add Sequential D&D Artifacts
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- Add the proposed [D&D NPC extraction and registry](dnd-npc-extraction.md) as
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the next sequential artifact. It defines canonical identity, aliases,
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descriptions, relationships, evidence, deterministic consolidation, and
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direct reuse as spell-pipeline reference material.
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- Add combat-turn extraction with explicit event and source-reference
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semantics. Use earlier NPC output as a reference to improve participant
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identity and consistency.
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- Add narrative extraction for scene summaries, party actions, and NPCs
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encountered when that output proves useful beyond the dedicated NPC artifact.
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- Define the preferred operational sequence for independent pipelines on the
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same transcript. The initial direction is NPCs first, followed by spells and
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combat turns as appropriate, with earlier JSON artifacts supplied to later
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runs as references.
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- Keep this sequencing operator- or script-driven initially. Do not require a
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general DAG or concurrent cross-lane reconciliation model.
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### Improve D&D Scene Classification
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- Extend scene annotations with classifications that downstream extractors can
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use, including reliable combat and narrative indicators.
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- Strengthen the scene prompt so every scene containing combat turns is marked
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as combat, and add validation capable of detecting missing or inconsistent
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combat classifications.
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- Allow the combat extractor to no-op for chunks that are not classified as
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combat, avoiding unnecessary model calls where practical.
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- Allow a narrative extractor to select the corresponding scene classification
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rather than processing every chunk indiscriminately.
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- Reassess whether one shared scene plan provides enough context for NPC,
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spell, combat, and narrative pipelines after these extractors have real-world
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usage. Add more complex chunking only in response to demonstrated failures.
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## Shared Normalization And Quality Work
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### Generic LLM-Assisted Deduplication
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- Add a reusable normalizer that asks an LLM to identify duplicate sets in a
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list and propose one replacement element for each set.
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- Define the minimum domain-neutral input contract, initially an ordered list
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whose elements have stable unique IDs. Artifact-kind registrations or
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adapters may expose that structure without moving domain rules into the
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generic package.
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- Keep mutation deterministic: parse and validate the model's duplicate groups,
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require every referenced ID to exist, reject overlapping or malformed groups,
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prevent unrelated insertion or deletion, and apply only approved replacement
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operations in code.
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- Preserve provenance needed for audit and downstream validation, and emit
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warnings describing every collapsed group.
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- Evaluate batching and context-window limits before applying the normalizer to
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large artifact collections.
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The model may use its own domain knowledge to judge semantic duplication; the
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generic implementation is responsible only for the common proposal contract,
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safety checks, and deterministic application of accepted changes.
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### Validation And Review
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- Add domain validators and production default chains alongside each new D&D
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artifact.
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- Add production LLM-backed validators only when a concrete review policy
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benefits from model judgment and deterministic checks are insufficient.
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- Add validator diagnostics and timing summaries if operators need more detail
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than the current [durable output bundle](../integrations/json-output.md)
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provides.
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- Add validator compatibility metadata if deployments need config-time proof
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that a validator is suitable for a particular stage, module, or artifact
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kind.
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- Add media-type validators when non-JSON artifact representations are
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introduced.
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## Reference And Sequential-Pipeline Evolution
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- Make prior-run artifacts easier to bind as references without changing the
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existing module-facing reference-item contract.
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- Add structured or parsed references, such as typed NPC registries, rosters,
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or spell catalogs, when opaque UTF-8 prompt material is no longer sufficient.
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- Add per-slot or per-chunk inclusion policies so large references are not
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repeated in every prompt unnecessarily.
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- Add token budgeting and model context-window management for reference
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content.
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- Add reference caching, preprocessing, summarization, embedding, or retrieval
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only when reference size and observed model behavior justify them.
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- Consider non-file reference producers for prior-run artifacts, derived
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summaries, or entity registries after manual sequential composition becomes
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burdensome.
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## Blue-Sky Platform And Operations
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These ideas are intentionally less specified. Promote one into an earlier
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section only after a concrete workflow, contract, and priority emerge.
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### Platform Extensions
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- Additional input adapters, such as Markdown or note-export formats.
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- Additional output encoders.
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- Concurrent cross-lane entity normalization or broader workflow composition.
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- Batching or specialized context-window controls for LLM-backed validators.
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### Distribution And Operations
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- Packaged release artifacts for alpha distribution.
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- A documented versioning and release process.
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- Optional generated example-output fixtures with a regeneration procedure.
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- Additional diagnostics or reporting views.
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### Workspace And Storage
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- Default-idempotent run behavior with an explicit force override.
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- Remote workspace storage.
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- Workspace garbage collection and archival policies.
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- Cross-machine checkpoint reuse.
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