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History
Claude aecfb8e0bb
feat(skills): wave-3 optimization — domain overhauls per newgen audit 
marketing: context-file unified on .claude/product-marketing-context.md;
ai-seo merged into aeo (2 new cited references, folder deleted); index +
marketing-ops routers rebuilt honestly; 24 orphan scripts wired with exact
CLIs; prompt-engineer-toolkit stub references rewritten with cited content;
Meta 20%-rule + GA4 terminology freshness; 5 zips + 3 planning docs removed

c-level-advisor: role registry 9->14 across all 6 routing surfaces; decision
memory unified on ~/.claude/decisions/{raw,approved}; onboarding schema
canonicalized; 12 phantom commands resolved; index repaired (33/37/68 real
counts); ma-playbook sourced + verification loop; 28 trigger descriptions

engineering(+team): agent-designer 279->76 lines and rag-architect 318->71
lines rebuilt around their tools (stale ada-002/pricing gone); release-manager
merged into changelog-generator (version_bumper + hotfix refs moved, crashing
release_planner dropped); 6 skills' orphan scripts wired; ms365 tools gained
real CLIs; 5 brochure skills de-filled; 4 unreferenced zips removed;
bundle counts trued (25->37, 23->32); 18 trigger descriptions

product/research/compliance/bizops: apple-hig-expert rebuilt around
hig_checker's real CLI with web-verified facts; notebooklm re-verified against
live product; 5 index skills converted to honest routers; research-summarizer
repaired with explicit lane statement; 8 over-1024 descriptions compressed;
9 sub-skills gained fenced CLI examples; GDPR one-month (Art. 12(3)) with
calendar-month deadline math; MDR PSUR table per Art. 86(1); 12 ra-qm zips
removed; 24 trigger descriptions

Verified: check_paths 0 findings; check_dual_publish 0 drifted; smoke 581/581;
check_plugin_json 77 OK; compileall rc=0; all descriptions <=1024 chars

https://claude.ai/code/session_019AJddAL1NADWMXsy1qNPQF
2026-06-11 03:58:41 +00:00
..
.claude-plugin chore(versioning): unify remaining 20 plugins to 2.9.0 2026-05-27 14:25:08 +00:00
agents fix: phantom-path sweep — 888 unresolvable references to zero 2026-06-10 14:33:00 +00:00
commands feat(research): patent + syllabus — Path-B batch 3 (specialty research-pack variants) 2026-05-16 02:06:56 +00:00
skills/syllabus feat(skills): wave-3 optimization — domain overhauls per newgen audit 2026-06-11 03:58:41 +00:00
README.md feat(research): patent + syllabus — Path-B batch 3 (specialty research-pack variants) 2026-05-16 02:06:56 +00:00

README.md

syllabus

Course supplementary reading list generator. Takes any course syllabus (PDF / DOCX / text / image) and produces a curated .docx of recent peer-reviewed papers via Consensus search, with plain-language summaries calibrated to audience level + Bloom-higher-order discussion questions tied to learning outcomes.

What this skill does

  1. Phase 0 grill-me (3 forcing Qs): syllabus input format + course audience + year range
  2. Phase 1: parse syllabus (PDF/DOCX/text/image) → extract topics + learning outcomes
  3. Phase 2: group topics into 6-12 sections + grill-me forcing checkpoint (proceed/merge/split/add/remove)
  4. Phase 3: targeted Consensus searches per section (1-2 queries each, sequential at 1 q/sec, applied-domain weaving)
  5. Phase 4: write summaries (audience-calibrated jargon) + discussion questions (Bloom higher-order)
  6. Phase 5: generate .docx via bundled JS script (scripts/generate_reading_list.js)
  7. Phase 6: deliver file + audit summary

Architectural pattern: bundled JS

This skill uses a bundled JavaScript helper script (scripts/generate_reading_list.js) for DOCX generation rather than inlining the 300+ lines of layout code in SKILL.md. Rationale:

  • DOCX generation logic is reusable + complex
  • Better separation of concerns: skill = orchestration + intelligence; script = mechanical document assembly
  • Token-efficient: skill doesn't re-derive layout each run
  • Easier to maintain and version

The skill orchestrates the pipeline and invokes the script with JSON input.

Sibling skill relationship

Part of the research pack (sibling of pulse, litreview, grants, patent, dossier). Shares Agent Integrity Rules. Adds:

  • Audience calibration — undergrad summaries define every term; grad summaries assume technical fluency
  • Applied-domain weaving — search "X applications" not just "X" (boosts relevance dramatically)
  • Bundled JS script pattern — first research-pack skill to use this layout

Source spec

megaprompts/10-syllabus-megaprompt.md (PR #657).

Plugin layout

research/syllabus/
├── .claude-plugin/plugin.json
├── README.md
├── agents/cs-syllabus.md
├── commands/cs-syllabus.md
└── skills/syllabus/
    ├── SKILL.md
    ├── references/
    │   ├── applied_domain_weaving.md       ← search-quality canon (7+ sources)
    │   ├── audience_calibration.md         ← undergrad vs grad summary jargon (7+ sources)
    │   └── bundled_script_pattern.md       ← why bundle vs inline (7+ sources)
    └── scripts/
        ├── citation_tracker.py             ← stdlib: Consensus three-count + 1s sequential
        ├── topic_grouper.py                ← stdlib: heuristic 6-12 section grouping
        ├── discussion_question_validator.py ← stdlib: Bloom higher-order quality check
        └── generate_reading_list.js        ← bundled Node.js: DOCX assembly (~300 lines)

Dependencies

  • Consensus MCP — Required for literature search
  • Node.js with docx package — Required (npm install docx)
  • Bundled script — scripts/generate_reading_list.js (shipped with skill, not external)
  • File reading — PDF reader / DOCX parser via pandoc / vision for images

License

MIT.