feat(clp): build full CLP agent roster, templates, and skills library

- 8 company agents: Lyra (intake), Selene (CEO), Atlas (research),
  Nova (publishing ops), Iris (author), Devon (dev editor),
  Lane (line editor), Cora (continuity editor)
- 19 additional templates (20 total): blog, recipe, short_story,
  book pipeline, ai_article, planning, boardroom, quick, project_index
- 5 skill guides: YA, Romance, SciFi, Blog, Recipe writing
- Rewritten charter and business plan

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

templates/ai_article_research.yml

@@ -0,0 +1,95 @@
+name: ai_article_research
+description: "Research the article series topic — live search + synthesis + spawn article plan task."
+debug: true
+system: agent_prompt
+
+agent_prompt:
+  - "= identity.md"
+  - "agent.rag.json"
+
+sections:
+  - agent
+  - project
+  - history
+  - rag
+  - prior_results
+  - message
+  - instructions
+
+builders:
+  prior_results: |
+    *** WEB SEARCH RESULTS ***
+    {steps[1].text}
+
+    (If the above is empty, use your expert training knowledge.)
+
+steps:
+  - type: think
+    hint: |
+      Read the project description and the message above carefully.
+      Identify the best search query to find current, real-world information on this topic.
+
+      State your reasoning, then on the last line write:
+      SEARCH QUERY: [your query here]
+
+      Query rules: 3-8 words. Specific. Current year preferred.
+
+  - type: tool
+    capability: Tool_WebSearcher
+    input_from: last_text
+
+  - type: think
+    hint: |
+      Using the search results above (or your training knowledge if unavailable), write a
+      RESEARCH BRIEF on the topic from the project description.
+
+      Cover as many relevant angles and subtopics as you can find real evidence for.
+      For each angle: what is happening, what problem it solves, one concrete result.
+
+      End with a SERIES RECOMMENDATION section proposing exactly 10 article topics.
+      For each topic: working title, target reader, the one thing they will learn.
+
+  - type: document
+    filename: "{{task_name_slug}}"
+
+  - type: package
+    packet_type: IntakeResponse
+    hint: |
+      Create exactly ONE follow-up task.
+
+      - task_name: "Plan Article Series"
+      - agent_name: "Atlas"
+      - task_type: "ai_article_plan"
+      - description: "Using the research deliverable, plan exactly 10 standalone articles for
+          this series. Each article is a 5-minute read (~800-1000 words) for the target audience
+          described in the project. You choose the topics based on the research. Then spawn 10
+          ai_article_write tasks for Iris."
+      - depends_on: ""
+    schema:
+      actions:
+        - type: create_task
+          task_name: "string"
+          agent_name: "string"
+          task_type: "string"
+          description: "string"
+          depends_on: "string"
+
+  - type: close
+    rag_update: true
+adjudication:
+  enabled: true
+  pass_threshold: 65
+  deliverable_type: coordination
+  criteria:
+    accuracy:
+      weight: 35
+      description: "Facts are correct and verifiable"
+    thoroughness:
+      weight: 30
+      description: "Topic covered in sufficient depth"
+    source_quality:
+      weight: 20
+      description: "Sources are credible and relevant"
+    organization:
+      weight: 15
+      description: "Findings are well-structured"