39 lines
1.4 KiB
Markdown
39 lines
1.4 KiB
Markdown
# Didactopus
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Didactopus is a local-first AI-assisted autodidactic mastery platform built around
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concept graphs, evaluator-driven evidence, adaptive planning, mastery ledgers,
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curriculum ingestion, and human review of generated draft packs.
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## This revision
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This revision adds a **graph-aware prerequisite analysis layer**.
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The goal is to inspect a pack not just as a set of files or even as a semantically
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plausible curriculum draft, but as an actual dependency graph whose structure may
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reveal deeper curation problems.
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## Why this matters
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A pack can be syntactically valid, cross-file coherent, and even semantically plausible,
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yet still have a concept graph that is hard to learn from or maintain. Typical examples:
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- prerequisite cycles
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- isolated concepts with no curricular integration
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- bottleneck concepts with too many downstream dependencies
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- suspiciously flat domains with almost no dependency structure
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- suspiciously deep chains suggesting over-fragmentation
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Those graph problems can still raise the activation-energy cost of using a pack,
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because they make learning paths harder to trust and revise.
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## What is included
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- prerequisite graph analysis module
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- cycle detection
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- isolated concept detection
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- bottleneck concept detection
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- flatness and chain-depth heuristics
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- graph findings included in import preview
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- UI panel for graph-analysis warnings
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- sample packs and tests
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