Neta Suggest Skill

Instructions

1. For research‑type tasks like “find me some ideas”, “what’s trending now”, or “filter content by a theme/category”, follow this flow:
2. Recommended path: browse categories → discover tags → validate paths → fetch content (the “Progressive Exploration” section below contains full command examples).
3. Before content creation, use this skill to research topics/tags/categories, then hand off to neta-creative for concrete creation.
4. When the user wants to like/comment or otherwise interact with specific works, switch to neta-community.

Core capabilities

1. suggest_keywords — keyword suggestions

Provide popular search keyword suggestions based on an input prefix, helping users discover directions of interest.

npx -y @talesofai/neta-skills@latest suggest_keywords --prefix "game" --size 20

Parameters

• --prefix: keyword prefix (required)
• --size: number of results, recommended 10–20 (optional)

Use cases

• User only has a vague idea.
• Explore trending topics and themes.
• Prepare for later precise filtering.

2. suggest_tags — related tag suggestions

Recommend related taxonomy tags based on a full keyword.

npx -y @talesofai/neta-skills@latest suggest_tags --keyword "character design" --size 15

Parameters

• --keyword: full keyword (required)
• --size: number of results, recommended 10–20 (optional)

Use cases

• Understand which tags surround a topic.
• Discover popular tags in a vertical domain.
• Choose suitable tags for publishing content.

3. suggest_categories — category navigation

Provide navigation suggestions in a 3‑level category hierarchy, supporting step‑by‑step exploration.

# Level 1 (top‑level categories)
npx -y @talesofai/neta-skills@latest suggest_categories --level 1

# Level 2 (requires parent path)
npx -y @talesofai/neta-skills@latest suggest_categories --level 2 --parent_path "Derivative Creation"

# Level 3 (most granular)
npx -y @talesofai/neta-skills@latest suggest_categories --level 3 --parent_path "Derivative Creation>Fan Works"

Parameters

• --level: category level (1/2/3) (required)
• --parent_path: parent category path, required when level > 1 (optional)

Example taxonomy

Level 1
├─ Derivative Creation
│  ├─ Fan Works (Level 2)
│  │  ├─ Honkai: Star Rail (Level 3)
│  │  └─ Genshin Impact (Level 3)
│  └─ Digital Art
├─ Lifestyle
└─ ...

Use cases

• Systematically understand the platform’s category structure.
• Navigate by following the tree to find specific domains.
• Validate candidate category paths.

4. validate_tax_path — validate taxonomy path

Validate that a taxonomy path string is valid before using it.

npx -y @talesofai/neta-skills@latest validate_tax_path --tax_path "Derivative Creation>Fan Works>Honkai: Star Rail"

Parameters

• --tax_path: full taxonomy path (required)

Use cases

• Validate paths before using them in filters.
• Ensure taxonomy paths are accurate.

5. suggest_content — intelligent content feed

Powerful content recommendation tool supporting three modes: recommend, search, and exact.

# Mode 1: recommend (broad exploration)
npx -y @talesofai/neta-skills@latest suggest_content \
  --page_index 0 \
  --page_size 20 \
  --scene agent_intent \
  --intent recommend

# Mode 2: search (keyword‑based)
npx -y @talesofai/neta-skills@latest suggest_content \
  --page_index 0 \
  --page_size 20 \
  --scene agent_intent \
  --intent search \
  --search_keywords "character,creativity"

# Mode 3: exact (category filtering)
npx -y @talesofai/neta-skills@latest suggest_content \
  --page_index 0 \
  --page_size 20 \
  --scene agent_intent \
  --intent exact \
  --tax_paths "Derivative Creation>Fan Works"

# Combined filters
npx -y @talesofai/neta-skills@latest suggest_content \
  --page_index 0 \
  --page_size 20 \
  --scene agent_intent \
  --intent search \
  --search_keywords "AI,painting" \
  --tax_paths "Digital Art>Concept Art" \
  --exclude_keywords "test,discarded"

Parameters

• --page_index: page index, starting from 0 (default 0)
• --page_size: items per page, 1–40 (default 20)
• --scene: scene identifier (default "agent_intent")
• --biz_trace_id: session trace ID (optional)
• --intent: recommend | search | exact (default recommend)
• --search_keywords: search keywords, separated by commas (optional)
• --tax_paths: taxonomy paths, separated by commas (optional)
• --tax_primaries: level‑1 categories (optional)
• --tax_secondaries: level‑2 categories (optional)
• --tax_tertiaries: level‑3 categories (optional)
• --exclude_keywords: excluded keywords (optional)
• --exclude_tax_paths: excluded taxonomy paths (optional)

Progressive exploration

Standard path (broad → narrow)

graph LR
    A[Browse categories] --> B[Discover tags]
    B --> C[Validate paths]
    C --> D[Fetch content]

Step 1: browse category system

# View all level‑1 categories
npx -y @talesofai/neta-skills@latest suggest_categories --level 1
# Example output: ["Derivative Creation", "Digital Art", "Lifestyle"]

# Dive into an interesting category
npx -y @talesofai/neta-skills@latest suggest_categories --level 2 --parent_path "Derivative Creation"
# Example: ["Fan Works", "Original Stories", "Interactive Fiction"]

Step 2: discover related tags

# Find tags from a keyword
npx -y @talesofai/neta-skills@latest suggest_tags --keyword "Fan Works" --size 15
# Example: ["Honkai: Star Rail", "Genshin Impact", "Arknights"]

# Use keyword suggestions to help
npx -y @talesofai/neta-skills@latest suggest_keywords --prefix "Hon" --size 10

Step 3: validate taxonomy path

npx -y @talesofai/neta-skills@latest validate_tax_path \
  --tax_path "Derivative Creation>Fan Works>Honkai: Star Rail"

Step 4: fetch recommended content

# Exact mode: filter by taxonomy only
npx -y @talesofai/neta-skills@latest suggest_content \
  --intent exact \
  --tax_paths "Derivative Creation>Fan Works>Honkai: Star Rail" \
  --page_size 20

# Search mode: combine keyword and taxonomy
npx -y @talesofai/neta-skills@latest suggest_content \
  --intent search \
  --search_keywords "Honkai: Star Rail,fan art" \
  --tax_paths "Derivative Creation>Fan Works" \
  --page_size 20

Common scenarios

Scenario 1: exploration without a clear goal

User is just browsing with no specific goal.

npx -y @talesofai/neta-skills@latest suggest_content \
  --intent recommend \
  --page_size 20

Tips:

• Avoid constraints at first.
• Let the system recommend based on popularity.
• Good for serendipitous discovery.

Scenario 2: vague interest direction

User has a rough topic in mind but not specific content.

# Step 1: keyword suggestions
npx -y @talesofai/neta-skills@latest suggest_keywords --prefix "game" --size 15

# Step 2: tag suggestions
npx -y @talesofai/neta-skills@latest suggest_tags --keyword "game" --size 15

# Step 3: search mode
npx -y @talesofai/neta-skills@latest suggest_content \
  --intent search \
  --search_keywords "Genshin Impact" \
  --page_size 20

Scenario 3: clear category goal

# Step 1: confirm taxonomy path
npx -y @talesofai/neta-skills@latest suggest_categories --level 1
npx -y @talesofai/neta-skills@latest suggest_categories --level 2 --parent_path "Derivative Creation"

# Step 2: validate path
npx -y @talesofai/neta-skills@latest validate_tax_path \
  --tax_path "Derivative Creation>Fan Works>Honkai: Star Rail"

# Step 3: exact filter
npx -y @talesofai/neta-skills@latest suggest_content \
  --intent exact \
  --tax_paths "Derivative Creation>Fan Works>Honkai: Star Rail" \
  --page_size 20

Scenario 4: pre‑creation research

# Step 1: understand popular tags
npx -y @talesofai/neta-skills@latest suggest_tags --keyword "character writing" --size 20

# Step 2: inspect related categories
npx -y @talesofai/neta-skills@latest suggest_categories --level 2 --parent_path "Derivative Creation"

# Step 3: view popular content under that category
npx -y @talesofai/neta-skills@latest suggest_content \
  --intent search \
  --search_keywords "character,setting" \
  --tax_paths "Derivative Creation>Fan Works" \
  --page_size 30

Scenario 5: excluding unwanted content

npx -y @talesofai/neta-skills@latest suggest_content \
  --intent search \
  --search_keywords "AI,painting" \
  --tax_paths "Digital Art" \
  --exclude_keywords "tutorial,ad" \
  --exclude_tax_paths "Digital Art>Courses" \
  --page_size 20

Parameter combination tips

Combination 1: keyword + taxonomy

npx -y @talesofai/neta-skills@latest suggest_content \
  --intent search \
  --search_keywords "video,editing" \
  --tax_paths "Digital Art>Video Production" \
  --page_size 20

Combination 2: multi‑level taxonomy

npx -y @talesofai/neta-skills@latest suggest_content \
  --intent exact \
  --tax_paths "Derivative Creation>Fan Works>Honkai: Star Rail" \
  --page_size 20

Combination 3: recommend + exclusions

npx -y @talesofai/neta-skills@latest suggest_content \
  --intent recommend \
  --exclude_keywords "tutorial, repost" \
  --exclude_tax_paths "Courses" \
  --page_size 20

Combination 4: pagination continuity

# Page 1
npx -y @talesofai/neta-skills@latest suggest_content \
  --page_index 0 \
  --page_size 20 \
  --intent search \
  --search_keywords "ideas" > /tmp/page0.json

# Extract biz_trace_id
BIZ_TRACE_ID=$(cat /tmp/page0.json | jq -r '.page_data.biz_trace_id')

# Page 2 (reuse same biz_trace_id)
npx -y @talesofai/neta-skills@latest suggest_content \
  --page_index 1 \
  --page_size 20 \
  --intent search \
  --search_keywords "ideas" \
  --biz_trace_id "$BIZ_TRACE_ID"

Output formats

suggest_keywords / suggest_tags / suggest_categories

{
  "suggestions": ["Suggestion 1", "Suggestion 2", "Suggestion 3"]
}

validate_tax_path

Valid path:

{
  "valid": true,
  "message": "Path is valid"
}

Invalid path:

{
  "valid": false,
  "message": "Error message"
}

suggest_content

{
  "module_list": [
    {
      "data_id": "module id",
      "module_id": "module type",
      "template_id": "template id",
      "json_data": {}
    }
  ],
  "page_data": {
    "has_next_page": true,
    "page_index": 0,
    "page_size": 20,
    "biz_trace_id": "trace id"
  }
}

Performance tips

1. Choose page_size wisely
   • Exploration: 10–15 for quick iteration.
   • Deep browsing: 20–30 to reduce page switches.
   • Precise lookup: 20–40 to fetch enough content at once.
2. Cache suggestions
   • Cache taxonomy and tag suggestions to avoid repeated calls.
3. Preload next‑level categories
   • While the user is viewing level‑1 categories, preload level‑2 categories in the background.
4. Batch‑validate taxonomy paths
   • Validate multiple candidate paths in parallel or via a simple script.

Debugging tips

1. Turn on debug logs for suggest_content to verify parameters.
2. Use exact mode with only taxonomy to test whether a path actually returns content.
3. Compare recommend, search, and exact with the same topic to understand their differences.

FAQ

Q1: What’s the difference between suggest_keywords and suggest_tags?

• suggest_keywords: prefix‑based fuzzy matching, good for early exploration.
• suggest_tags: relevance‑based matching on full keywords, more precise.

Q2: Why does validate_tax_path succeed but suggest_content return empty?

Possible reasons:

1. The taxonomy path is valid but currently has no content.
2. Wrong intent mode (e.g., using recommend instead of exact).
3. Other filters conflict.

Q3: How to choose the right intent?

Intent	Use case	Required params
recommend	Browsing without clear goal	None
search	Keyword‑driven search	search_keywords
exact	Strict category filtering	tax_paths or taxonomy params

Q4: How to use exclude_keywords and exclude_tax_paths?

Use them to aggressively filter noise content, but note they can significantly reduce result count.

Q5: How to maintain biz_trace_id across pages?

Always keep and reuse the first biz_trace_id returned for a given query instead of chaining from page to page.

Summary

Key points for using the exploration skill:

1. Progressive exploration: Categories → Tags → Validation → Content.
2. Intent selection: recommend for aimless browsing, search for keyword queries, exact for strict taxonomy.
3. Combination filters: combine keywords with taxonomy for precise control.
4. Exclusions: use exclude_* parameters judiciously to filter noise.
5. Session continuity: maintain a consistent biz_trace_id for stable paging behavior.

By following these practices, you can explore and discover high‑quality content on the platform efficiently.