Neta Suggest

Neta API research and recommendation skill — provide keyword/tag/category suggestions, validate taxonomy paths, and power multi‑mode content feeds, supportin...

Security Scan

The skill's instructions match a keyword/tag/category CLI tool, but the package omits a declared required credential (NETA_TOKEN) and asks you to globally install an npm package — these mismatches and install instructions deserve caution before installing or supplying secrets.

Purpose & Capability

The SKILL.md describes a taxonomy/tag/content-suggestion CLI (neta-cli) and the commands/invocations in the document align with that purpose. However, the registry metadata claims no required env vars or binaries while the instructions explicitly require NETA_TOKEN and a neta-cli/npm package, so the metadata and runtime instructions are inconsistent.

Instruction Scope

The runtime instructions are scoped to using neta-cli commands (suggest_keywords/tags/categories/content) and installing an npm package. The SKILL.md does not instruct the agent to read unrelated files, system paths, or to exfiltrate arbitrary data; it stays within the described content-recommendation domain.

Install Mechanism

There is no formal install spec in the registry; the SKILL.md tells users to globally install @talesofai/neta-skills (npm/pnpm). Global npm installs are common for CLIs but they run code from the npm registry (postinstall scripts, etc.). This is expected for a CLI skill but is a moderate-risk action that should be verified (check the package source, maintainers, and published files before installing globally).

Credentials

The instructions require a NETA_TOKEN environment variable, but the skill metadata lists no required env vars or primary credential. Requesting a token is proportionate for an API-backed CLI, but the omission from the declared requirements is a mismatch that reduces transparency and could lead to inadvertent token exposure. Confirm what NETA_TOKEN provides access to and whether its scope is limited before supplying it.

Persistence & Privilege

The skill is not marked always:true and does not declare modifications to system-wide configs or other skills. It is user-invocable and may be invoked autonomously by the agent (platform default), which is normal for skills.

What to consider before installing

This skill appears to be a CLI wrapper for a content/taxonomy recommendation service and the instructions are consistent with that. Before installing or providing credentials: 1) Verify the package @talesofai/neta-skills exists on npm and inspect its repository/homepage and recent publish history; 2) Confirm what NETA_TOKEN is (which service it authenticates, what permissions/scopes it grants) and avoid supplying a broad or long-lived token; 3) Prefer installing in a controlled environment (container or non-production machine) or avoid global (-g) installs until you audit the package; 4) Ask the skill author or registry for missing metadata (required env vars and homepage/source) — the metadata should list NETA_TOKEN if it is required; 5) If you must proceed, limit token scope and rotate/revoke it if you later remove the skill or suspect misuse.

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.

Prerequisites

Make sure the NETA_TOKEN environment variable is set.

Install the latest version of the Neta CLI:

neta-cli --version
0.8.0

npm i @talesofai/neta-skills@latest -g

pnpm add -g @talesofai/neta-skills@latest

Core capabilities

1. suggest_keywords — keyword suggestions

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

neta-cli 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.

neta-cli 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)
neta-cli suggest_categories --level 1

# Level 2 (requires parent path)
neta-cli suggest_categories --level 2 --parent_path "Derivative Creation"

# Level 3 (most granular)
neta-cli 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.

neta-cli 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)
neta-cli suggest_content \
  --page_index 0 \
  --page_size 20 \
  --scene agent_intent \
  --intent recommend

# Mode 2: search (keyword‑based)
neta-cli suggest_content \
  --page_index 0 \
  --page_size 20 \
  --scene agent_intent \
  --intent search \
  --search_keywords "character,creativity"

# Mode 3: exact (category filtering)
neta-cli suggest_content \
  --page_index 0 \
  --page_size 20 \
  --scene agent_intent \
  --intent exact \
  --tax_paths "Derivative Creation>Fan Works"

# Combined filters
neta-cli 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
neta-cli suggest_categories --level 1
# Example output: ["Derivative Creation", "Digital Art", "Lifestyle"]

# Dive into an interesting category
neta-cli 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
neta-cli suggest_tags --keyword "Fan Works" --size 15
# Example: ["Honkai: Star Rail", "Genshin Impact", "Arknights"]

# Use keyword suggestions to help
neta-cli suggest_keywords --prefix "Hon" --size 10

Step 3: validate taxonomy path

neta-cli validate_tax_path \
  --tax_path "Derivative Creation>Fan Works>Honkai: Star Rail"

Step 4: fetch recommended content

# Exact mode: filter by taxonomy only
neta-cli suggest_content \
  --intent exact \
  --tax_paths "Derivative Creation>Fan Works>Honkai: Star Rail" \
  --page_size 20

# Search mode: combine keyword and taxonomy
neta-cli 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.

neta-cli 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
neta-cli suggest_keywords --prefix "game" --size 15

# Step 2: tag suggestions
neta-cli suggest_tags --keyword "game" --size 15

# Step 3: search mode
neta-cli suggest_content \
  --intent search \
  --search_keywords "Genshin Impact" \
  --page_size 20

Scenario 3: clear category goal

# Step 1: confirm taxonomy path
neta-cli suggest_categories --level 1
neta-cli suggest_categories --level 2 --parent_path "Derivative Creation"

# Step 2: validate path
neta-cli validate_tax_path \
  --tax_path "Derivative Creation>Fan Works>Honkai: Star Rail"

# Step 3: exact filter
neta-cli 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
neta-cli suggest_tags --keyword "character writing" --size 20

# Step 2: inspect related categories
neta-cli suggest_categories --level 2 --parent_path "Derivative Creation"

# Step 3: view popular content under that category
neta-cli suggest_content \
  --intent search \
  --search_keywords "character,setting" \
  --tax_paths "Derivative Creation>Fan Works" \
  --page_size 30

Scenario 5: excluding unwanted content

neta-cli 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

neta-cli suggest_content \
  --intent search \
  --search_keywords "video,editing" \
  --tax_paths "Digital Art>Video Production" \
  --page_size 20

Combination 2: multi‑level taxonomy

neta-cli suggest_content \
  --intent exact \
  --tax_paths "Derivative Creation>Fan Works>Honkai: Star Rail" \
  --page_size 20

Combination 3: recommend + exclusions

neta-cli suggest_content \
  --intent recommend \
  --exclude_keywords "tutorial, repost" \
  --exclude_tax_paths "Courses" \
  --page_size 20

Combination 4: pagination continuity

# Page 1
neta-cli 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)
neta-cli 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.