Algo Rec Hybrid

What it does

When your agent uses it

• The user needs to overcome single-method limitations
• Combine collaborative and content-based filtering
• Build a production recommendation pipeline — even if they say combine recommendation approaches
• Best recommendation architecture

Example prompts

• “combine recommendation approaches”
• “best recommendation architecture”
• “cold start plus personalization”
• “/algo-rec-hybrid”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

1. 1Input Validation
2. 2Core Algorithm
3. 3Verification
4. 4Output

What it can do on your machine

Read from SKILL.md and the folder at commit 4e7f4f8. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  No scripts in the folder and no shell commands in SKILL.md (its code samples are json).

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Algo Rec Hybrid loads about 1.1k tokens when it runs, and up to ~7k if it reads all its reference files. Until then it costs about 102 tokens; SKILL.md has 411 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~102

When it runs · the whole SKILL.md, loaded when a task matches

~1.1k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from asgard-ai-platform/skills at commit 4e7f4f8, republished under its MIT licence (© asgard-ai-platform). 411 words, ~1,105 tokens.

name

algo-rec-hybrid

description

Design hybrid recommendation systems combining multiple strategies for improved accuracy. Use this skill when the user needs to overcome single-method limitations, combine collaborative and content-based filtering, or build a production recommendation pipeline — even if they say 'combine recommendation approaches', 'best recommendation architecture', or 'cold start plus personalization'.

metadata.category

WP-36 推薦系統

metadata.tags

recommendation, hybrid, ensemble, system-design

IRON LAW: Hybrid Adds Value ONLY With Complementary Strengths
Combining two systems with the SAME weakness amplifies the weakness.
CF fails on cold start + content-based fails on cold start = hybrid
STILL fails on cold start. Choose components that cover each other's gaps.

{
  "recommendations": [{"item_id": "789", "score": 0.91, "sources": {"cf": 0.85, "content": 0.95}, "method": "weighted"}],
  "metadata": {"architecture": "weighted", "weights": {"cf": 0.6, "content": 0.4}, "coverage": 0.78}
}

© asgard-ai-platform, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in algo-rec-hybrid of asgard-ai-platform/skills.

• SKILL.md
• examples/sample_scenario.md
• references/ab-testing-recs.md
• references/architecture-selection.md

Open the folder on GitHubat commit 4e7f4f8