ML Research

Deep-dive into ML topics using verified framework documentation, not stale training data.

Grounding

Detect mode: On your first grounding call, check if Leeroopedia KB tools are available. If they return results, use KB mode. If unavailable or auth fails, use Web mode.

CRITICAL SELF-CHECK before Phase 1: If KB auth fails, your FIRST action must be WebFetch — not text output. Do NOT write any prose, explanation, or "I know this topic" before completing at least 3 WebFetch calls. The phrases "I know this topic well" and "I have deep knowledge of these" appeared in real failures and are disqualifying errors.

MANDATORY SEQUENCE when KB fails: (1) Make 3+ WebFetch calls. (2) Confirm you have content from those calls. (3) ONLY THEN write your first line of prose. If your response starts with ANY text before tool calls, you have already failed. There is no "but I know this one" exception.

KB mode: Call search_knowledge (2-4 parallel queries) → get_page on top results → synthesize. Cite as [PageID].

Web mode: WebFetch official docs (3-5 pages) → WebFetch GitHub README/examples → WebFetch model cards for each model mentioned → synthesize. Cite as [source](URL). Start response with: > Grounding: Web mode — citations from official docs.

Web mode is NOT optional. If KB auth fails, you MUST immediately switch to web mode and fetch real documentation. Do not proceed without at least 3 WebFetch calls returning real content.

ZERO-TOLERANCE RULE: If your first instinct is "I know this topic well enough" — that is the exact moment you MUST ground. The following phrases (and synonyms) are BANNED: "well within my training knowledge", "I can answer this from memory", "this is a well-known topic", "I have deep knowledge", "I have extensive knowledge", "I know these methods well", "I'm familiar with". They are the #1 failure mode of this skill. Every response requires fetched sources, no exceptions. If you catch yourself composing ANY sentence that explains why grounding is unnecessary, STOP and make a WebFetch call instead.