Revision of license acknowledgements process, artifacts.

docs/faq.md

@@ -163,6 +163,7 @@ generates:
 - learner outputs in `examples/ocw-information-entropy-run/`
 - a repo-local skill bundle in `skills/ocw-information-entropy-agent/`
 - an agentic skill-usage demo in `examples/ocw-information-entropy-skill-demo/`
+- compliance artifacts including `pack_compliance_manifest.json` and `source_inventory.yaml`
 
 ## What visualizations exist today?
 
@@ -218,4 +219,3 @@ via Codex to confirm functionality, fix bugs, and update
 documentation. Elsberry provided goals, direction, operational
 principles, and orchestration, and generative AI has provided pretty
 much the rest.
-

docs/license-compliance.md

@@ -36,6 +36,12 @@ A derived pack should carry:
 - share_alike_required
 - noncommercial_only
 
+The recommended route in this repository is:
+
+1. maintain a `sources.yaml` inventory for the source set
+2. generate `pack_compliance_manifest.json`
+3. keep `license_attribution.json` for human-facing attribution details
+
 ## MIT OCW-specific pattern
 
 For MIT OpenCourseWare-derived packs, treat the course material as licensed content while separately recording:
@@ -43,3 +49,5 @@ For MIT OpenCourseWare-derived packs, treat the course material as licensed cont
 - image/video exceptions
 - linked-content exceptions
 - any asset not safely covered by the course-level reuse assumption
+
+The MIT OCW Information and Entropy demo in this repository follows that pattern and can be used as the reference implementation.

docs/mit-ocw-course-guide.md

@@ -0,0 +1,93 @@
+# Working With Other MIT OCW Courses
+
+This is the recommended pattern for bringing more MIT OpenCourseWare courses into Didactopus.
+
+## Goal
+
+Use MIT OCW as a structured source for learning, while preserving:
+
+- attribution
+- license references
+- adaptation status
+- noncommercial/share-alike flags
+- a place to record excluded third-party content when it appears
+
+## Minimal workflow
+
+1. Pick a course and collect the specific pages you are actually using.
+2. Create a local derived source file for reproducible ingestion.
+3. Create a `sources.yaml` inventory beside that source file.
+4. Run the ingestion/demo pipeline and emit a `pack_compliance_manifest.json`.
+5. Review the generated pack before treating it as reusable teaching material.
+
+## Recommended directory shape
+
+For a new MIT OCW-derived example, mirror the existing pattern:
+
+```text
+examples/<course-slug>/
+  course-source.md
+  sources.yaml
+```
+
+The corresponding generated outputs should include:
+
+```text
+domain-packs/<course-slug>/
+  license_attribution.json
+  pack_compliance_manifest.json
+  source_inventory.yaml
+```
+
+## What goes in `sources.yaml`
+
+Record each course page or resource page that materially informed the generated pack.
+
+At minimum include:
+
+- `source_id`
+- `title`
+- `url`
+- `publisher`
+- `creator`
+- `license_id`
+- `license_url`
+- `retrieved_at`
+- `adapted`
+- `attribution_text`
+- `excluded_from_upstream_license`
+- `exclusion_notes`
+
+Use `examples/ocw-information-entropy/sources.yaml` as the concrete model.
+
+## When to add excluded-source records
+
+Add explicit excluded records when:
+
+- the course page points to third-party figures or readings
+- the page itself warns that a particular asset is excluded from the main course license
+- you want the record preserved even though you do not reuse the asset
+
+That is the route for acknowledging future sources that require special handling.
+
+## Practical advice for course selection
+
+Good first OCW candidates:
+
+- courses with a strong week-by-week or unit-by-unit structure
+- courses with stable textual descriptions, readings, or assignments
+- courses where you can summarize the progression into a single local source file
+
+Harder candidates:
+
+- courses whose value is mostly in embedded media
+- courses with many third-party handouts or linked readings
+- courses with weak textual structure
+
+## Current repo reference
+
+The MIT OCW Information and Entropy demo is the reference implementation of this pattern:
+
+- source file: `examples/ocw-information-entropy/6-050j-information-and-entropy.md`
+- source inventory: `examples/ocw-information-entropy/sources.yaml`
+- generated pack: `domain-packs/mit-ocw-information-entropy/`

docs/mit-ocw-notes.md

@@ -7,7 +7,9 @@ MIT OpenCourseWare material is a good fit for Didactopus demos, but it needs exp
 The MIT OCW Information and Entropy demo stores:
 
 - a local derived source file in `examples/ocw-information-entropy/`
+- a `sources.yaml` source inventory beside that file
 - attribution and rights notes in the generated pack
+- a generated `pack_compliance_manifest.json` in the generated pack
 - generated learner outputs in `examples/ocw-information-entropy-run/`
 - a repo-local skill bundle in `skills/ocw-information-entropy-agent/`
 
@@ -27,6 +29,9 @@ That means Didactopus should:
 When building from MIT OCW sources:
 
 - record the course page and any unit/resource pages used
+- keep those records in a per-course `sources.yaml` inventory
 - separate core MIT OCW material from excluded third-party items if they appear
 - keep generated pack content clearly marked as adapted/derived
-- include attribution artifacts with the emitted pack
+- include attribution and compliance artifacts with the emitted pack
+
+For the full workflow, see `docs/mit-ocw-course-guide.md`.

domain-packs/mit-ocw-information-entropy/concepts.yaml

@@ -0,0 +1,420 @@
+concepts:
+- id: mit-ocw-6-050j-information-and-entropy
+  title: MIT OCW 6.050J Information and Entropy
+  description: 'Source: MIT OpenCourseWare 6.050J Information and Entropy, Spring
+    2008.
+
+    Attribution: adapted from the OCW course overview, unit sequence, and assigned
+    textbook references.'
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: information
+  title: Information
+  description: Candidate concept extracted from lesson 'MIT OCW 6.050J Information
+    and Entropy'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: entropy
+  title: Entropy
+  description: Candidate concept extracted from lesson 'MIT OCW 6.050J Information
+    and Entropy'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: source
+  title: Source
+  description: Candidate concept extracted from lesson 'MIT OCW 6.050J Information
+    and Entropy'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: opencourseware
+  title: OpenCourseWare
+  description: Candidate concept extracted from lesson 'MIT OCW 6.050J Information
+    and Entropy'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: spring
+  title: Spring
+  description: Candidate concept extracted from lesson 'MIT OCW 6.050J Information
+    and Entropy'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: attribution
+  title: Attribution
+  description: Candidate concept extracted from lesson 'MIT OCW 6.050J Information
+    and Entropy'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: counting-and-probability
+  title: Counting and Probability
+  description: '- Objective: Explain how counting arguments, probability spaces, and
+    random variables support later information-theory results.
+
+    - Exercise: Derive a simple counting argument for binary strings and compute an
+    event probability.
+
+    This lesson i'
+  prerequisites:
+  - mit-ocw-6-050j-information-and-entropy
+  mastery_signals: []
+  mastery_profile: {}
+- id: counting
+  title: Counting
+  description: Candidate concept extracted from lesson 'Counting and Probability'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: probability
+  title: Probability
+  description: Candidate concept extracted from lesson 'Counting and Probability'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: objective
+  title: Objective
+  description: Candidate concept extracted from lesson 'Counting and Probability'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: explain
+  title: Explain
+  description: Candidate concept extracted from lesson 'Counting and Probability'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: exercise
+  title: Exercise
+  description: Candidate concept extracted from lesson 'Counting and Probability'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: derive
+  title: Derive
+  description: Candidate concept extracted from lesson 'Counting and Probability'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: this
+  title: This
+  description: Candidate concept extracted from lesson 'Counting and Probability'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: random
+  title: Random
+  description: Candidate concept extracted from lesson 'Counting and Probability'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: shannon-entropy
+  title: Shannon Entropy
+  description: '- Objective: Explain Shannon Entropy as a measure of uncertainty and
+    compare high-entropy and low-entropy sources.
+
+    - Exercise: Compute the entropy of a Bernoulli source and interpret the result.
+
+    This lesson centers Shannon Entropy, Surprise'
+  prerequisites:
+  - counting-and-probability
+  mastery_signals: []
+  mastery_profile: {}
+- id: shannon
+  title: Shannon
+  description: Candidate concept extracted from lesson 'Shannon Entropy'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: compute
+  title: Compute
+  description: Candidate concept extracted from lesson 'Shannon Entropy'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: bernoulli
+  title: Bernoulli
+  description: Candidate concept extracted from lesson 'Shannon Entropy'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: mutual-information
+  title: Mutual Information
+  description: '- Objective: Explain Mutual Information and relate it to dependence
+    between signals.
+
+    - Exercise: Compare independent variables with dependent variables using mutual-information
+    reasoning.
+
+    This lesson introduces Mutual Information, Dependenc'
+  prerequisites:
+  - shannon-entropy
+  mastery_signals: []
+  mastery_profile: {}
+- id: mutual
+  title: Mutual
+  description: Candidate concept extracted from lesson 'Mutual Information'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: compare
+  title: Compare
+  description: Candidate concept extracted from lesson 'Mutual Information'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: dependence
+  title: Dependence
+  description: Candidate concept extracted from lesson 'Mutual Information'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: data-compression
+  title: Data Compression
+  description: '- Objective: Explain lossless compression in terms of entropy and
+    typical structure.
+
+    - Exercise: Describe when compression succeeds and when it fails on already-random
+    data.
+
+    This lesson covers Data Compression, Redundancy, and Efficient Rep'
+  prerequisites:
+  - mutual-information
+  mastery_signals: []
+  mastery_profile: {}
+- id: data
+  title: Data
+  description: Candidate concept extracted from lesson 'Data Compression'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: compression
+  title: Compression
+  description: Candidate concept extracted from lesson 'Data Compression'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: describe
+  title: Describe
+  description: Candidate concept extracted from lesson 'Data Compression'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: redundancy
+  title: Redundancy
+  description: Candidate concept extracted from lesson 'Data Compression'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: huffman-coding
+  title: Huffman Coding
+  description: '- Objective: Explain Huffman Coding and justify why shorter codewords
+    should track more likely symbols.
+
+    - Exercise: Build a Huffman code for a small source alphabet.
+
+    This lesson focuses on Huffman Coding, Prefix Codes, and Expected Length.'
+  prerequisites:
+  - data-compression
+  mastery_signals: []
+  mastery_profile: {}
+- id: huffman
+  title: Huffman
+  description: Candidate concept extracted from lesson 'Huffman Coding'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: coding
+  title: Coding
+  description: Candidate concept extracted from lesson 'Huffman Coding'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: build
+  title: Build
+  description: Candidate concept extracted from lesson 'Huffman Coding'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: prefix
+  title: Prefix
+  description: Candidate concept extracted from lesson 'Huffman Coding'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: channel-capacity
+  title: Channel Capacity
+  description: '- Objective: Explain Channel Capacity as a limit on reliable communication
+    over noisy channels.
+
+    - Exercise: State why reliable transmission above capacity is impossible in the
+    long run.
+
+    This lesson develops Channel Capacity, Reliable Commun'
+  prerequisites:
+  - huffman-coding
+  mastery_signals: []
+  mastery_profile: {}
+- id: channel
+  title: Channel
+  description: Candidate concept extracted from lesson 'Channel Capacity'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: capacity
+  title: Capacity
+  description: Candidate concept extracted from lesson 'Channel Capacity'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: state
+  title: State
+  description: Candidate concept extracted from lesson 'Channel Capacity'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: reliable
+  title: Reliable
+  description: Candidate concept extracted from lesson 'Channel Capacity'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: channel-coding
+  title: Channel Coding
+  description: '- Objective: Explain how Channel Coding adds structure that protects
+    messages against noise.
+
+    - Exercise: Contrast uncoded transmission with coded transmission on a noisy channel.
+
+    This lesson connects Channel Coding, Decoding, and Reliabilit'
+  prerequisites:
+  - channel-capacity
+  mastery_signals: []
+  mastery_profile: {}
+- id: contrast
+  title: Contrast
+  description: Candidate concept extracted from lesson 'Channel Coding'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: decoding
+  title: Decoding
+  description: Candidate concept extracted from lesson 'Channel Coding'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: error-correcting-codes
+  title: Error Correcting Codes
+  description: '- Objective: Explain how Error Correcting Codes detect or correct
+    symbol corruption.
+
+    - Exercise: Describe a simple parity-style code and its limits.
+
+    This lesson covers Error Correcting Codes, Parity, and Syndrome-style reasoning.
+    The learne'
+  prerequisites:
+  - channel-coding
+  mastery_signals: []
+  mastery_profile: {}
+- id: error
+  title: Error
+  description: Candidate concept extracted from lesson 'Error Correcting Codes'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: correcting
+  title: Correcting
+  description: Candidate concept extracted from lesson 'Error Correcting Codes'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: codes
+  title: Codes
+  description: Candidate concept extracted from lesson 'Error Correcting Codes'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: cryptography-and-information-hiding
+  title: Cryptography and Information Hiding
+  description: '- Objective: Explain the relationship between secrecy, information
+    leakage, and coded communication.
+
+    - Exercise: Compare a secure scheme with a weak one in terms of revealed information.
+
+    This lesson combines Cryptography, Information Leakag'
+  prerequisites:
+  - error-correcting-codes
+  mastery_signals: []
+  mastery_profile: {}
+- id: cryptography
+  title: Cryptography
+  description: Candidate concept extracted from lesson 'Cryptography and Information
+    Hiding'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: hiding
+  title: Hiding
+  description: Candidate concept extracted from lesson 'Cryptography and Information
+    Hiding'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: thermodynamics-and-entropy
+  title: Thermodynamics and Entropy
+  description: '- Objective: Explain how thermodynamic entropy relates to, and differs
+    from, Shannon entropy.
+
+    - Exercise: Compare the two entropy notions and identify what is preserved across
+    the analogy.
+
+    This lesson connects Thermodynamics, Entropy, and P'
+  prerequisites:
+  - cryptography-and-information-hiding
+  mastery_signals: []
+  mastery_profile: {}
+- id: thermodynamics
+  title: Thermodynamics
+  description: Candidate concept extracted from lesson 'Thermodynamics and Entropy'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: course-synthesis
+  title: Course Synthesis
+  description: '- Objective: Synthesize the course by connecting entropy, coding,
+    reliability, and physical interpretation in one coherent narrative.
+
+    - Exercise: Produce a final study guide that links source coding, channel coding,
+    secrecy, and thermodynam'
+  prerequisites:
+  - thermodynamics-and-entropy
+  mastery_signals: []
+  mastery_profile: {}
+- id: course
+  title: Course
+  description: Candidate concept extracted from lesson 'Course Synthesis'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: synthesis
+  title: Synthesis
+  description: Candidate concept extracted from lesson 'Course Synthesis'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: synthesize
+  title: Synthesize
+  description: Candidate concept extracted from lesson 'Course Synthesis'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}
+- id: produce
+  title: Produce
+  description: Candidate concept extracted from lesson 'Course Synthesis'.
+  prerequisites: []
+  mastery_signals: []
+  mastery_profile: {}

domain-packs/mit-ocw-information-entropy/conflict_report.md

@@ -0,0 +1,3 @@
+# Conflict Report
+
+- none

domain-packs/mit-ocw-information-entropy/license_attribution.json

@@ -0,0 +1,10 @@
+{
+  "rights_note": "Derived from MIT OpenCourseWare 6.050J Information and Entropy (Spring 2008). Retain MIT OCW attribution and applicable Creative Commons terms before redistribution.",
+  "sources": [
+    {
+      "source_path": "/home/netuser/dev/Didactopustry1/examples/ocw-information-entropy/6-050j-information-and-entropy.md",
+      "source_type": "markdown",
+      "title": "6 050J Information And Entropy"
+    }
+  ]
+}

domain-packs/mit-ocw-information-entropy/pack.yaml

@@ -0,0 +1,14 @@
+name: mit-ocw-information-and-entropy
+display_name: MIT OCW Information and Entropy
+version: 0.1.0-draft
+schema_version: '1'
+didactopus_min_version: 0.1.0
+didactopus_max_version: 0.9.99
+description: Draft topic pack generated from multi-course inputs for 'MIT OCW Information
+  and Entropy'.
+author: MIT OCW derived demo
+license: CC BY-NC-SA 4.0
+dependencies: []
+overrides: []
+profile_templates: {}
+cross_pack_links: []

domain-packs/mit-ocw-information-entropy/pack_compliance_manifest.json

@@ -0,0 +1,20 @@
+{
+  "pack_id": "mit-ocw-information-and-entropy",
+  "display_name": "MIT OCW Information and Entropy",
+  "derived_from_sources": [
+    "mit-ocw-6-050j-course-home",
+    "mit-ocw-6-050j-unit-8-textbook",
+    "mit-ocw-6-050j-unit-13-textbook"
+  ],
+  "attribution_required": true,
+  "share_alike_required": true,
+  "noncommercial_only": true,
+  "restrictive_flags": [
+    "share-alike",
+    "noncommercial"
+  ],
+  "redistribution_notes": [
+    "Derived redistributable material may need to remain under the same license family.",
+    "Derived redistributable material may be limited to noncommercial use."
+  ]
+}

domain-packs/mit-ocw-information-entropy/projects.yaml

@@ -0,0 +1 @@
+projects: []

domain-packs/mit-ocw-information-entropy/review_report.md

@@ -0,0 +1,59 @@
+# Review Report
+
+- Module 'Imported from MARKDOWN' has no explicit exercises; mastery signals may be weak.
+- Concept 'MIT OCW 6.050J Information and Entropy' has no extracted mastery signals; review manually.
+- Concept 'Information' has no extracted mastery signals; review manually.
+- Concept 'Entropy' has no extracted mastery signals; review manually.
+- Concept 'Source' has no extracted mastery signals; review manually.
+- Concept 'OpenCourseWare' has no extracted mastery signals; review manually.
+- Concept 'Spring' has no extracted mastery signals; review manually.
+- Concept 'Attribution' has no extracted mastery signals; review manually.
+- Concept 'Counting and Probability' has no extracted mastery signals; review manually.
+- Concept 'Counting' has no extracted mastery signals; review manually.
+- Concept 'Probability' has no extracted mastery signals; review manually.
+- Concept 'Objective' has no extracted mastery signals; review manually.
+- Concept 'Explain' has no extracted mastery signals; review manually.
+- Concept 'Exercise' has no extracted mastery signals; review manually.
+- Concept 'Derive' has no extracted mastery signals; review manually.
+- Concept 'This' has no extracted mastery signals; review manually.
+- Concept 'Random' has no extracted mastery signals; review manually.
+- Concept 'Shannon Entropy' has no extracted mastery signals; review manually.
+- Concept 'Shannon' has no extracted mastery signals; review manually.
+- Concept 'Compute' has no extracted mastery signals; review manually.
+- Concept 'Bernoulli' has no extracted mastery signals; review manually.
+- Concept 'Mutual Information' has no extracted mastery signals; review manually.
+- Concept 'Mutual' has no extracted mastery signals; review manually.
+- Concept 'Compare' has no extracted mastery signals; review manually.
+- Concept 'Dependence' has no extracted mastery signals; review manually.
+- Concept 'Data Compression' has no extracted mastery signals; review manually.
+- Concept 'Data' has no extracted mastery signals; review manually.
+- Concept 'Compression' has no extracted mastery signals; review manually.
+- Concept 'Describe' has no extracted mastery signals; review manually.
+- Concept 'Redundancy' has no extracted mastery signals; review manually.
+- Concept 'Huffman Coding' has no extracted mastery signals; review manually.
+- Concept 'Huffman' has no extracted mastery signals; review manually.
+- Concept 'Coding' has no extracted mastery signals; review manually.
+- Concept 'Build' has no extracted mastery signals; review manually.
+- Concept 'Prefix' has no extracted mastery signals; review manually.
+- Concept 'Channel Capacity' has no extracted mastery signals; review manually.
+- Concept 'Channel' has no extracted mastery signals; review manually.
+- Concept 'Capacity' has no extracted mastery signals; review manually.
+- Concept 'State' has no extracted mastery signals; review manually.
+- Concept 'Reliable' has no extracted mastery signals; review manually.
+- Concept 'Channel Coding' has no extracted mastery signals; review manually.
+- Concept 'Contrast' has no extracted mastery signals; review manually.
+- Concept 'Decoding' has no extracted mastery signals; review manually.
+- Concept 'Error Correcting Codes' has no extracted mastery signals; review manually.
+- Concept 'Error' has no extracted mastery signals; review manually.
+- Concept 'Correcting' has no extracted mastery signals; review manually.
+- Concept 'Codes' has no extracted mastery signals; review manually.
+- Concept 'Cryptography and Information Hiding' has no extracted mastery signals; review manually.
+- Concept 'Cryptography' has no extracted mastery signals; review manually.
+- Concept 'Hiding' has no extracted mastery signals; review manually.
+- Concept 'Thermodynamics and Entropy' has no extracted mastery signals; review manually.
+- Concept 'Thermodynamics' has no extracted mastery signals; review manually.
+- Concept 'Course Synthesis' has no extracted mastery signals; review manually.
+- Concept 'Course' has no extracted mastery signals; review manually.
+- Concept 'Synthesis' has no extracted mastery signals; review manually.
+- Concept 'Synthesize' has no extracted mastery signals; review manually.
+- Concept 'Produce' has no extracted mastery signals; review manually.

domain-packs/mit-ocw-information-entropy/roadmap.yaml

@@ -0,0 +1,17 @@
+stages:
+- id: stage-1
+  title: Imported from MARKDOWN
+  concepts:
+  - mit-ocw-6-050j-information-and-entropy
+  - counting-and-probability
+  - shannon-entropy
+  - mutual-information
+  - data-compression
+  - huffman-coding
+  - channel-capacity
+  - channel-coding
+  - error-correcting-codes
+  - cryptography-and-information-hiding
+  - thermodynamics-and-entropy
+  - course-synthesis
+  checkpoint: []

domain-packs/mit-ocw-information-entropy/rubrics.yaml

@@ -0,0 +1,6 @@
+rubrics:
+- id: draft-rubric
+  title: Draft Rubric
+  criteria:
+  - correctness
+  - explanation

domain-packs/mit-ocw-information-entropy/source_inventory.yaml

@@ -0,0 +1,39 @@
+sources:
+  - source_id: mit-ocw-6-050j-course-home
+    title: MIT OpenCourseWare 6.050J Information and Entropy course home
+    url: https://ocw.mit.edu/courses/6-050j-information-and-entropy-spring-2008/
+    publisher: Massachusetts Institute of Technology
+    creator: MIT OpenCourseWare
+    license_id: CC BY-NC-SA 4.0
+    license_url: https://creativecommons.org/licenses/by-nc-sa/4.0/
+    retrieved_at: "2026-03-14"
+    adapted: true
+    attribution_text: Derived in part from MIT OpenCourseWare 6.050J Information and Entropy course materials used under CC BY-NC-SA 4.0.
+    excluded_from_upstream_license: false
+    exclusion_notes: ""
+
+  - source_id: mit-ocw-6-050j-unit-8-textbook
+    title: MIT OpenCourseWare 6.050J Information and Entropy Unit 8 textbook/resource page
+    url: https://ocw.mit.edu/courses/6-050j-information-and-entropy-spring-2008/resources/mit6_050js08_textbook_1/
+    publisher: Massachusetts Institute of Technology
+    creator: MIT OpenCourseWare
+    license_id: CC BY-NC-SA 4.0
+    license_url: https://creativecommons.org/licenses/by-nc-sa/4.0/
+    retrieved_at: "2026-03-14"
+    adapted: true
+    attribution_text: Derived in part from MIT OpenCourseWare 6.050J Information and Entropy course materials used under CC BY-NC-SA 4.0.
+    excluded_from_upstream_license: false
+    exclusion_notes: ""
+
+  - source_id: mit-ocw-6-050j-unit-13-textbook
+    title: MIT OpenCourseWare 6.050J Information and Entropy Unit 13 textbook/resource page
+    url: https://ocw.mit.edu/courses/6-050j-information-and-entropy-spring-2008/resources/mit6_050js08_textbook_2/
+    publisher: Massachusetts Institute of Technology
+    creator: MIT OpenCourseWare
+    license_id: CC BY-NC-SA 4.0
+    license_url: https://creativecommons.org/licenses/by-nc-sa/4.0/
+    retrieved_at: "2026-03-14"
+    adapted: true
+    attribution_text: Derived in part from MIT OpenCourseWare 6.050J Information and Entropy course materials used under CC BY-NC-SA 4.0.
+    excluded_from_upstream_license: false
+    exclusion_notes: ""

examples/ocw-information-entropy-run/run_summary.json

@@ -2,6 +2,7 @@
   "course_source": "/home/netuser/dev/Didactopustry1/examples/ocw-information-entropy/6-050j-information-and-entropy.md",
   "pack_dir": "/home/netuser/dev/Didactopustry1/domain-packs/mit-ocw-information-entropy",
   "skill_dir": "/home/netuser/dev/Didactopustry1/skills/ocw-information-entropy-agent",
+  "source_inventory": "/home/netuser/dev/Didactopustry1/examples/ocw-information-entropy/sources.yaml",
   "review_flags": [
     "Module 'Imported from MARKDOWN' has no explicit exercises; mastery signals may be weak.",
     "Concept 'MIT OCW 6.050J Information and Entropy' has no extracted mastery signals; review manually.",
@@ -89,5 +90,26 @@
     "mit-ocw-information-and-entropy::shannon-entropy",
     "mit-ocw-information-and-entropy::thermodynamics-and-entropy"
   ],
-  "artifact_count": 11
+  "artifact_count": 11,
+  "compliance_manifest": "/home/netuser/dev/Didactopustry1/domain-packs/mit-ocw-information-entropy/pack_compliance_manifest.json",
+  "compliance": {
+    "pack_id": "mit-ocw-information-and-entropy",
+    "display_name": "MIT OCW Information and Entropy",
+    "derived_from_sources": [
+      "mit-ocw-6-050j-course-home",
+      "mit-ocw-6-050j-unit-8-textbook",
+      "mit-ocw-6-050j-unit-13-textbook"
+    ],
+    "attribution_required": true,
+    "share_alike_required": true,
+    "noncommercial_only": true,
+    "restrictive_flags": [
+      "share-alike",
+      "noncommercial"
+    ],
+    "redistribution_notes": [
+      "Derived redistributable material may need to remain under the same license family.",
+      "Derived redistributable material may be limited to noncommercial use."
+    ]
+  }
 }

examples/ocw-information-entropy/sources.yaml

@@ -0,0 +1,39 @@
+sources:
+  - source_id: mit-ocw-6-050j-course-home
+    title: MIT OpenCourseWare 6.050J Information and Entropy course home
+    url: https://ocw.mit.edu/courses/6-050j-information-and-entropy-spring-2008/
+    publisher: Massachusetts Institute of Technology
+    creator: MIT OpenCourseWare
+    license_id: CC BY-NC-SA 4.0
+    license_url: https://creativecommons.org/licenses/by-nc-sa/4.0/
+    retrieved_at: "2026-03-14"
+    adapted: true
+    attribution_text: Derived in part from MIT OpenCourseWare 6.050J Information and Entropy course materials used under CC BY-NC-SA 4.0.
+    excluded_from_upstream_license: false
+    exclusion_notes: ""
+
+  - source_id: mit-ocw-6-050j-unit-8-textbook
+    title: MIT OpenCourseWare 6.050J Information and Entropy Unit 8 textbook/resource page
+    url: https://ocw.mit.edu/courses/6-050j-information-and-entropy-spring-2008/resources/mit6_050js08_textbook_1/
+    publisher: Massachusetts Institute of Technology
+    creator: MIT OpenCourseWare
+    license_id: CC BY-NC-SA 4.0
+    license_url: https://creativecommons.org/licenses/by-nc-sa/4.0/
+    retrieved_at: "2026-03-14"
+    adapted: true
+    attribution_text: Derived in part from MIT OpenCourseWare 6.050J Information and Entropy course materials used under CC BY-NC-SA 4.0.
+    excluded_from_upstream_license: false
+    exclusion_notes: ""
+
+  - source_id: mit-ocw-6-050j-unit-13-textbook
+    title: MIT OpenCourseWare 6.050J Information and Entropy Unit 13 textbook/resource page
+    url: https://ocw.mit.edu/courses/6-050j-information-and-entropy-spring-2008/resources/mit6_050js08_textbook_2/
+    publisher: Massachusetts Institute of Technology
+    creator: MIT OpenCourseWare
+    license_id: CC BY-NC-SA 4.0
+    license_url: https://creativecommons.org/licenses/by-nc-sa/4.0/
+    retrieved_at: "2026-03-14"
+    adapted: true
+    attribution_text: Derived in part from MIT OpenCourseWare 6.050J Information and Entropy course materials used under CC BY-NC-SA 4.0.
+    excluded_from_upstream_license: false
+    exclusion_notes: ""

skills/ocw-information-entropy-agent/assets/generated/pack/pack_compliance_manifest.json

@@ -0,0 +1,20 @@
+{
+  "pack_id": "mit-ocw-information-and-entropy",
+  "display_name": "MIT OCW Information and Entropy",
+  "derived_from_sources": [
+    "mit-ocw-6-050j-course-home",
+    "mit-ocw-6-050j-unit-8-textbook",
+    "mit-ocw-6-050j-unit-13-textbook"
+  ],
+  "attribution_required": true,
+  "share_alike_required": true,
+  "noncommercial_only": true,
+  "restrictive_flags": [
+    "share-alike",
+    "noncommercial"
+  ],
+  "redistribution_notes": [
+    "Derived redistributable material may need to remain under the same license family.",
+    "Derived redistributable material may be limited to noncommercial use."
+  ]
+}

skills/ocw-information-entropy-agent/assets/generated/pack/source_inventory.yaml

@@ -0,0 +1,39 @@
+sources:
+  - source_id: mit-ocw-6-050j-course-home
+    title: MIT OpenCourseWare 6.050J Information and Entropy course home
+    url: https://ocw.mit.edu/courses/6-050j-information-and-entropy-spring-2008/
+    publisher: Massachusetts Institute of Technology
+    creator: MIT OpenCourseWare
+    license_id: CC BY-NC-SA 4.0
+    license_url: https://creativecommons.org/licenses/by-nc-sa/4.0/
+    retrieved_at: "2026-03-14"
+    adapted: true
+    attribution_text: Derived in part from MIT OpenCourseWare 6.050J Information and Entropy course materials used under CC BY-NC-SA 4.0.
+    excluded_from_upstream_license: false
+    exclusion_notes: ""
+
+  - source_id: mit-ocw-6-050j-unit-8-textbook
+    title: MIT OpenCourseWare 6.050J Information and Entropy Unit 8 textbook/resource page
+    url: https://ocw.mit.edu/courses/6-050j-information-and-entropy-spring-2008/resources/mit6_050js08_textbook_1/
+    publisher: Massachusetts Institute of Technology
+    creator: MIT OpenCourseWare
+    license_id: CC BY-NC-SA 4.0
+    license_url: https://creativecommons.org/licenses/by-nc-sa/4.0/
+    retrieved_at: "2026-03-14"
+    adapted: true
+    attribution_text: Derived in part from MIT OpenCourseWare 6.050J Information and Entropy course materials used under CC BY-NC-SA 4.0.
+    excluded_from_upstream_license: false
+    exclusion_notes: ""
+
+  - source_id: mit-ocw-6-050j-unit-13-textbook
+    title: MIT OpenCourseWare 6.050J Information and Entropy Unit 13 textbook/resource page
+    url: https://ocw.mit.edu/courses/6-050j-information-and-entropy-spring-2008/resources/mit6_050js08_textbook_2/
+    publisher: Massachusetts Institute of Technology
+    creator: MIT OpenCourseWare
+    license_id: CC BY-NC-SA 4.0
+    license_url: https://creativecommons.org/licenses/by-nc-sa/4.0/
+    retrieved_at: "2026-03-14"
+    adapted: true
+    attribution_text: Derived in part from MIT OpenCourseWare 6.050J Information and Entropy course materials used under CC BY-NC-SA 4.0.
+    excluded_from_upstream_license: false
+    exclusion_notes: ""

skills/ocw-information-entropy-agent/assets/generated/run/run_summary.json

@@ -2,6 +2,7 @@
   "course_source": "/home/netuser/dev/Didactopustry1/examples/ocw-information-entropy/6-050j-information-and-entropy.md",
   "pack_dir": "/home/netuser/dev/Didactopustry1/domain-packs/mit-ocw-information-entropy",
   "skill_dir": "/home/netuser/dev/Didactopustry1/skills/ocw-information-entropy-agent",
+  "source_inventory": "/home/netuser/dev/Didactopustry1/examples/ocw-information-entropy/sources.yaml",
   "review_flags": [
     "Module 'Imported from MARKDOWN' has no explicit exercises; mastery signals may be weak.",
     "Concept 'MIT OCW 6.050J Information and Entropy' has no extracted mastery signals; review manually.",
@@ -89,5 +90,26 @@
     "mit-ocw-information-and-entropy::shannon-entropy",
     "mit-ocw-information-and-entropy::thermodynamics-and-entropy"
   ],
-  "artifact_count": 11
+  "artifact_count": 11,
+  "compliance_manifest": "/home/netuser/dev/Didactopustry1/domain-packs/mit-ocw-information-entropy/pack_compliance_manifest.json",
+  "compliance": {
+    "pack_id": "mit-ocw-information-and-entropy",
+    "display_name": "MIT OCW Information and Entropy",
+    "derived_from_sources": [
+      "mit-ocw-6-050j-course-home",
+      "mit-ocw-6-050j-unit-8-textbook",
+      "mit-ocw-6-050j-unit-13-textbook"
+    ],
+    "attribution_required": true,
+    "share_alike_required": true,
+    "noncommercial_only": true,
+    "restrictive_flags": [
+      "share-alike",
+      "noncommercial"
+    ],
+    "redistribution_notes": [
+      "Derived redistributable material may need to remain under the same license family.",
+      "Derived redistributable material may be limited to noncommercial use."
+    ]
+  }
 }

src/didactopus/ocw_information_entropy_demo.py

@@ -5,6 +5,7 @@ from pathlib import Path
 
 from .agentic_loop import AgenticStudentState, integrate_attempt
 from .artifact_registry import validate_pack
+from .course_ingestion_compliance import build_pack_compliance_manifest, load_sources, write_manifest
 from .document_adapters import adapt_document
 from .evaluator_pipeline import LearnerAttempt
 from .graph_builder import build_concept_graph
@@ -123,11 +124,13 @@ def _write_skill_bundle(
 
 def run_ocw_information_entropy_demo(
     course_source: str | Path,
+    source_inventory: str | Path,
     pack_dir: str | Path,
     run_dir: str | Path,
     skill_dir: str | Path,
 ) -> dict:
     course_source = Path(course_source)
+    source_inventory = Path(source_inventory)
     pack_dir = Path(pack_dir)
     run_dir = Path(run_dir)
     skill_dir = Path(skill_dir)
@@ -150,6 +153,11 @@ def run_ocw_information_entropy_demo(
         conflicts=[],
     )
     write_draft_pack(draft, pack_dir)
+    if source_inventory.exists():
+        inventory = load_sources(source_inventory)
+        compliance_manifest = build_pack_compliance_manifest(draft.pack["name"], draft.pack["display_name"], inventory)
+        write_manifest(compliance_manifest, pack_dir / "pack_compliance_manifest.json")
+        (pack_dir / "source_inventory.yaml").write_text(source_inventory.read_text(encoding="utf-8"), encoding="utf-8")
 
     validation = validate_pack(pack_dir)
     if not validation.is_valid:
@@ -183,6 +191,7 @@ def run_ocw_information_entropy_demo(
         "course_source": str(course_source),
         "pack_dir": str(pack_dir),
         "skill_dir": str(skill_dir),
+        "source_inventory": str(source_inventory),
         "review_flags": list(ctx.review_flags),
         "concept_count": len(ctx.concepts),
         "target_concept": target_key,
@@ -190,6 +199,10 @@ def run_ocw_information_entropy_demo(
         "mastered_concepts": sorted(state.mastered_concepts),
         "artifact_count": len(state.artifacts),
     }
+    compliance_path = pack_dir / "pack_compliance_manifest.json"
+    if compliance_path.exists():
+        summary["compliance_manifest"] = str(compliance_path)
+        summary["compliance"] = json.loads(compliance_path.read_text(encoding="utf-8"))
     (run_dir / "run_summary.json").write_text(json.dumps(summary, indent=2), encoding="utf-8")
 
     _write_skill_bundle(skill_dir, pack_dir, run_dir, concept_path, summary["mastered_concepts"])
@@ -205,6 +218,10 @@ def main() -> None:
         "--course-source",
         default=str(root / "examples" / "ocw-information-entropy" / "6-050j-information-and-entropy.md"),
     )
+    parser.add_argument(
+        "--source-inventory",
+        default=str(root / "examples" / "ocw-information-entropy" / "sources.yaml"),
+    )
     parser.add_argument(
         "--pack-dir",
         default=str(root / "domain-packs" / "mit-ocw-information-entropy"),
@@ -221,6 +238,7 @@ def main() -> None:
 
     summary = run_ocw_information_entropy_demo(
         course_source=args.course_source,
+        source_inventory=args.source_inventory,
         pack_dir=args.pack_dir,
         run_dir=args.run_dir,
         skill_dir=args.skill_dir,

tests/test_artifact_registry.py

@@ -28,4 +28,4 @@ def test_dependency_resolution() -> None:
     results = discover_domain_packs(["domain-packs"])
     errors = check_pack_dependencies(results)
     assert any("depends on missing pack 'nonexistent-pack'" in err for err in errors)
-    assert not any("bayes-extension" in err for err in errors and "foundations-statistics" in err)
+    assert not any("bayes-extension" in err and "foundations-statistics" in err for err in errors)

tests/test_ocw_information_entropy_demo.py

@@ -7,12 +7,14 @@ def test_ocw_information_entropy_demo_generates_pack_and_skill(tmp_path: Path) -
     root = Path(__file__).resolve().parents[1]
     summary = run_ocw_information_entropy_demo(
         course_source=root / "examples" / "ocw-information-entropy" / "6-050j-information-and-entropy.md",
+        source_inventory=root / "examples" / "ocw-information-entropy" / "sources.yaml",
         pack_dir=tmp_path / "pack",
         run_dir=tmp_path / "run",
         skill_dir=tmp_path / "skill",
     )
 
     assert (tmp_path / "pack" / "pack.yaml").exists()
+    assert (tmp_path / "pack" / "pack_compliance_manifest.json").exists()
     assert (tmp_path / "run" / "capability_profile.json").exists()
     assert (tmp_path / "skill" / "SKILL.md").exists()
     assert summary["target_concept"].endswith("thermodynamics-and-entropy")

tests/test_ocw_skill_agent_demo.py

@@ -0,0 +1,33 @@
+from pathlib import Path
+
+from didactopus.ocw_skill_agent_demo import (
+    evaluate_submission_with_skill,
+    load_ocw_skill_context,
+    run_ocw_skill_agent_demo,
+)
+
+
+def test_run_ocw_skill_agent_demo(tmp_path: Path) -> None:
+    root = Path(__file__).resolve().parents[1]
+    payload = run_ocw_skill_agent_demo(
+        root / "skills" / "ocw-information-entropy-agent",
+        tmp_path,
+    )
+
+    assert (tmp_path / "skill_demo.json").exists()
+    assert (tmp_path / "skill_demo.md").exists()
+    assert payload["study_plan"]["steps"]
+    assert payload["evaluation"]["verdict"] in {"acceptable", "needs_revision"}
+
+
+def test_skill_demo_flags_weak_submission() -> None:
+    root = Path(__file__).resolve().parents[1]
+    context = load_ocw_skill_context(root / "skills" / "ocw-information-entropy-agent")
+    result = evaluate_submission_with_skill(
+        context,
+        "channel-capacity",
+        "Channel capacity is good.",
+    )
+
+    assert result["verdict"] == "needs_revision"
+    assert "Rework the answer" in result["follow_up"]