* refactor(skills): clean up bundled skill set + add environments: relevance gate Bundled skills cleanup pass plus a new offer-time relevance gate. Removals (redundant / dead): - spotify (covered by the spotify plugin's 7 native tools) - linear (covered by `hermes mcp install linear`) - kanban-codex-lane, debugging-hermes-tui-commands - empty category markers: diagramming, gifs, inference-sh, mlops/training, mlops/vector-databases - domain (stale orphan dup of optional/research/domain-intel) Bundled -> optional: - baoyu-article-illustrator, baoyu-comic, creative-ideation, pixel-art - dspy, subagent-driven-development - minecraft-modpack-server, pokemon-player - hermes-s6-container-supervision (-> optional/devops) Consolidation: - webhook-subscriptions + native-mcp folded into the hermes-agent skill as references/webhooks.md + references/native-mcp.md with SKILL.md pointers - writing-plans merged into plan (v2.0.0); related_skills + prose refs updated New: environments: frontmatter gate (agent/skill_utils.skill_matches_environment) - Offer-time relevance filter (kanban / docker / s6), parallel to platforms:. - Wired into the 3 OFFER surfaces only (prompt_builder skills index, skills_tool.list_skills, skill_commands slash discovery). - Explicit loads (skill_view, --skills preload) intentionally BYPASS it, so load-bearing force-loads like the kanban dispatcher's `--skills kanban-worker` always resolve. Verified via E2E. - kanban-orchestrator/kanban-worker tagged environments: [kanban]; hermes-s6-container-supervision tagged environments: [s6] + platforms: [linux]. Validation: 8/8 E2E gating assertions (incl force-load invariant); 442 targeted tests green (agent, skills_tool, skill_commands, kanban worker). * docs: regenerate skill catalogs + pages for the bundled cleanup Regenerated per-skill doc pages, catalogs, and sidebar to match the skill moves/removals in the parent commit. Moved skills' pages relocate bundled -> optional (history preserved); removed skills' pages deleted; edited skills' pages refreshed (hermes-agent now embeds the webhook + native-mcp reference pointers). zh-Hans i18n mirror: stale bundled pages and catalog rows for moved/removed skills pruned (new optional translations land via the translation pipeline). * test: drop regression test for removed kanban-codex-lane skill The kanban-codex-lane skill was removed in the bundled-skills cleanup; its dedicated regression test read the now-deleted SKILL.md and failed with FileNotFoundError on CI shard 6.
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Comic Content Analysis Framework
Deep analysis framework for transforming source content into effective visual storytelling.
Purpose
Before creating a comic, thoroughly analyze the source material to:
- Identify the target audience and their needs
- Determine what value the comic will deliver
- Extract narrative potential for visual storytelling
- Plan character arcs and key moments
Analysis Dimensions
1. Core Content (Understanding "What")
Central Message
- What is the single most important idea readers should take away?
- Can you express it in one sentence?
Key Concepts
- What are the essential concepts readers must understand?
- How should these concepts be visualized?
- Which concepts need simplified explanations?
Content Structure
- How is the source material organized?
- What is the natural narrative arc?
- Where are the climax and turning points?
Evidence & Examples
- What concrete examples, data, or stories support the main ideas?
- Which examples translate well to visual panels?
- What can be shown rather than told?
2. Context & Background (Understanding "Why")
Source Origin
- Who created this content? What is their perspective?
- What was the original purpose?
- Is there bias to be aware of?
Historical/Cultural Context
- When and where does the story take place?
- What background knowledge do readers need?
- What period-specific visual elements are required?
Underlying Assumptions
- What does the source assume readers already know?
- What implicit beliefs or values are present?
- Should the comic challenge or reinforce these?
3. Audience Analysis
Primary Audience
- Who will read this comic?
- What is their existing knowledge level?
- What are their interests and motivations?
Secondary Audiences
- Who else might benefit from this comic?
- How might their needs differ?
Reader Questions
- What questions will readers have?
- What misconceptions might they bring?
- What "aha moments" can we create?
4. Value Proposition
Knowledge Value
- What will readers learn?
- What new perspectives will they gain?
- How will this change their understanding?
Emotional Value
- What emotions should readers feel?
- What connections will they make with characters?
- What will make this memorable?
Practical Value
- Can readers apply what they learn?
- What actions might this inspire?
- What conversations might it spark?
5. Narrative Potential
Story Arc Candidates
- What natural narratives exist in the content?
- Where is the conflict or tension?
- What transformations occur?
Character Potential
- Who are the key figures?
- What are their motivations and obstacles?
- How do they change throughout?
Visual Opportunities
- What scenes have strong visual potential?
- Where can abstract concepts become concrete images?
- What metaphors can be visualized?
Dramatic Moments
- What are the breakthrough/revelation moments?
- Where are the emotional peaks?
- What creates tension and release?
6. Adaptation Considerations
What to Keep
- Essential facts and ideas
- Key quotes or moments
- Core emotional beats
What to Simplify
- Complex explanations
- Dense technical details
- Lengthy descriptions
What to Expand
- Brief mentions that deserve more attention
- Implied emotions or relationships
- Visual details not in source
What to Omit
- Tangential information
- Redundant examples
- Content that doesn't serve the narrative
Output Format
Analysis results should be saved to analysis.md with:
- YAML Front Matter: Metadata (title, topic, time_span, source_language, user_language, aspect_ratio, recommended_page_count, recommended_art, recommended_tone, recommended_layout)
- Target Audience: Primary, secondary, tertiary audiences with their needs
- Value Proposition: What readers will gain (knowledge, emotional, practical)
- Core Themes: Table with theme, narrative potential, visual opportunity
- Key Figures & Story Arcs: Character profiles with arcs, visual identity, key moments
- Content Signals: Style and layout recommendations based on content type
- Recommended Approaches: Narrative approaches ranked by suitability
YAML Front Matter Example
---
title: "Alan Turing: The Father of Computing"
topic: alan-turing-biography
time_span: 1912-1954
source_language: en
user_language: zh # User-specified or detected from conversation
aspect_ratio: "3:4"
recommended_page_count: 16
recommended_art: ligne-claire # ligne-claire|manga|realistic|ink-brush|chalk
recommended_tone: neutral # neutral|warm|dramatic|romantic|energetic|vintage|action
recommended_layout: mixed # standard|cinematic|dense|splash|mixed|webtoon
---
Language Fields
| Field | Description |
|---|---|
source_language |
Detected language of source content |
user_language |
Output language for comic (user-specified option > conversation language > source_language) |
Analysis Checklist
Before proceeding to storyboard:
- Can I state the core message in one sentence?
- Do I know exactly who will read this comic?
- Have I identified at least 3 ways this comic provides value?
- Are there clear protagonists with compelling arcs?
- Have I found at least 5 visually powerful moments?
- Do I understand what to keep, simplify, expand, and omit?
- Have I identified the emotional peaks and valleys?