google-search

Use when the user wants help finding information through Google or Google-style web search and expects more than raw links. Handle current facts, public-information lookups, official documents, tutorials, reports, tools, materials, or source discovery by classifying the search goal, generating precise queries, executing search, ranking sources, cross-checking key claims, and returning a concise conclusion plus reusable search strings. Also use for programmer-specific searches (error debugging, official docs, GitHub code search, Stack Overflow, RFC lookup, benchmarks).

Google Search

Quick Reference

If you need to…Go to
Mode budgets: Quick (1–2 queries) / Standard (3–5) / Deep (5–8)§6 Execution Mode Gate
Search for Go / Python / JS errors, API docs, or RFCsLoad references/programmer-search-patterns.md
Search Chinese-language sources (Baidu, Zhihu, WeChat)Load references/chinese-search-ecosystem.md
Search on a fast-changing / conflict-prone topicLoad references/high-conflict-topics.md
Evaluate source quality or resolve conflicting sourcesLoad references/source-evaluation.md

Overview

Use this skill to turn vague search requests into a disciplined search-and-verification workflow. Default to doing the search work for the user first, then give them the reusable Google queries and refinement strategy if they want to continue manually.

Mandatory Gates

Gates execute in strict serial order. Any gate failure blocks all subsequent steps.

1) Scope         2) Ambiguity     3) Evidence      4) Language
   Classification → Resolution   → Requirements  → Detection
   │                │               │               │
   category+goal    unclear?        what proof?     EN/CN/Both?
   → classify       → STOP+ASK     → define chain  → set strategy
        │                │               │               │
        5) Source       6) Mode         7) Budget       8) Execution
           Path       →    Selection  →    Control   →    Integrity
           │               │               │               │
           official first? Quick/Std/Deep  max queries     actually searched?
           → rank sources  → auto-select   → enforce       → report honestly

1) Scope Classification Gate

Map the request into one primary category and one goal before writing any query.

Categories:

  • Information: news, facts, latest status, company or person updates
  • Knowledge: tutorials, best practices, explainers, research, official docs
  • Materials: PDFs, reports, templates, images, datasets, downloads
  • Tools: apps, services, plugins, utilities, alternatives
  • Public-information lookup: public records, bios, publications, profiles
  • Programmer search: error debugging, API docs, code examples, benchmarks, RFCs

Goals: Know | Learn | Create | Complete a task

2) Ambiguity Resolution Gate

STOP and ASK if:

  • The request maps to multiple categories (e.g., "help me with Redis")
  • The goal is ambiguous (know vs. learn vs. troubleshoot)
  • The target entity is ambiguous (e.g., "苹果" — fruit or Apple Inc.?)
  • The time scope is unclear for time-sensitive topics

Confirm category, goal, and scope before proceeding.

3) Evidence Requirements Gate

Before writing any query, define the minimum evidence chain needed to support the conclusion at the expected confidence level. This determines what to search for, not just how to search.

Conclusion TypeMinimum Evidence ChainTarget Confidence
Single factual claim (date, version, status)1 official or primary sourceHigh
Best practice or recommendation1 official basis + 1 practitioner reportMedium-High
Numeric claim or statistic1 primary dataset + 1 independent cross-checkHigh (with labels)
Technology comparison or ranking2+ independent benchmarks with disclosed methodologyMedium
Person or entity identification2+ independent public records with cross-matchMedium (inference unless explicit)
Disputed or fast-moving topic3+ sources from different tiers + conflict resolutionTiered with ranges

How to use: After classifying the question (Gate 1) and resolving ambiguity (Gate 2), map it to one row above. The evidence chain sets the minimum sources you must find — do not write the conclusion until the chain is satisfied, or explicitly degrade (see Honest Degradation).

If the evidence chain cannot be satisfied after the query budget is exhausted, degrade to Partial or Blocked rather than presenting an unsupported conclusion.

4) Language Detection Gate

Determine the primary search language based on the evidence chain requirements:

  • English-first: global technology, open-source, RFCs, vendor docs, academic papers
  • Chinese-first: China-specific policy, domestic companies, local regulations
  • Both (paired queries): engineering best practices, production experience, mixed topics

Read references/chinese-search-ecosystem.md when Chinese sources are needed.

5) Source Path Gate

Choose the source path before exploring broad results. Prefer the source, not commentary about the source.

Default ranking:

  1. Official site, official account, original publisher, original document
  2. Primary data, paper, PDF, filing, release notes, standards body
  3. Reputable media or institutions that cite original material correctly
  4. High-quality specialist communities or vertical sites
  5. Aggregators, reposts, SEO pages, and summaries

Use domain constraints early when the right source family is obvious.

Read references/source-evaluation.md for full ranking and conflict-resolution rules.

6) Execution Mode Gate

Auto-select mode based on task signals, then state the selection in output:

Signal→ Mode
Simple factual question with likely definitive answerQuick
User says "quick", "fast", "just tell me"Quick
Default for most searchesStandard
Troubleshooting, best practices, production experienceStandard
User says "thorough", "comprehensive", "deep dive"Deep
High-conflict topic (war, election, disaster)Deep
Multi-source comparison or research reportDeep

Mode definitions:

ModeQueriesCross-checkOutput
Quick1–2Not required if source is official/primaryConclusion + 1–2 queries
Standard3–52 independent sources for key claimsFull 4-section output
Deep5–83+ sources, explicit conflict resolutionFull output + source comparison table

If the user explicitly requests a specific mode, use that mode.

Quick Mode Fast Path: When signals clearly point to Quick mode (simple factual question, single-answer expected), collapse gates 1–8 into a single-line internal check and skip gate execution log in the output. Do NOT output per-gate logs for Quick mode — go straight to queries and conclusion.

7) Budget Control Gate

Enforce bounded query budgets per mode:

  • Quick: max 2 queries
  • Standard: max 5 queries (Round 1: 3, Round 2: 2)
  • Deep: max 8 queries (Round 1: 3, Round 2: 3, Round 3: 2)

If the budget is exhausted without a satisfactory answer, stop searching and report what was found, what remains uncertain, and what next strategy would resolve the gap.

Read references/ai-search-and-termination.md for escalation and termination rules.

8) Execution Integrity Gate

Never claim a search was performed unless it actually ran.

  • If a query was not executed, do not present hypothetical results.
  • If a source was not opened, do not claim to have verified its content.
  • Never report "confirmed" when the evidence is only from snippets.
  • Distinguish between "I found X" and "search snippet mentions X."

Workflow

After passing all gates:

  1. Build Query Sets — Always prepare at least three query variants (Primary, Precision, Expansion). Read references/query-patterns.md for category-specific patterns. For programmer searches, read references/programmer-search-patterns.md.

  2. Execute and Triage — Search with the strongest query first, then refine based on results. Open first-party or original sources before commentary. If the first pass is weak, reformulate by changing one variable at a time (see Refinement Loop in query-patterns.md).

  3. Evaluate and Cross-Check — Treat results as candidate evidence, not truth. For each important source, judge: originality, recency, directness, specificity, independence. Read references/source-evaluation.md for full evaluation protocol.

  4. Write the Answer — Follow the Output Contract below.

For high-conflict and high-change topics (wars, elections, disasters), read references/high-conflict-topics.md for stricter scope-locking and source-tiering.

Content Access Resilience

WebFetch may fail to extract content from sites behind Cloudflare, AWS WAF, or JavaScript-heavy SPAs. When this happens:

Failure Detection

Recognize blocked responses:

  • HTTP 403 Forbidden or empty body from a known-content page
  • Response contains "Just a moment...", "Checking your browser", "Enable JavaScript"
  • Extracted text is < 30 words from a page that should be content-rich

Fallback Chain

When WebFetch fails, try these in order:

  1. Firecrawl — If the firecrawl-scrape skill is available, use it (handles JS rendering and anti-bot)
  2. Snippet-only mode — Use search snippets as evidence, but explicitly label: "Based on search snippet, not full page content"
  3. Platform-specific — Tell the user which platform to search directly (e.g., "This StackOverflow page requires browser access")

Reporting

When degraded to snippet-only, the answer must:

  • Set degradation level to Partial (not Full)
  • State which sources could not be fully accessed
  • Lower confidence labels accordingly
  • Provide the direct URL so the user can verify manually

Anti-Examples — DO NOT Do These

  1. Presenting search snippets as verified facts — a snippet is a preview, not a confirmed source. Open the page and verify before citing.

    BAD: "According to search results, the answer is X."
    GOOD: "According to [specific source, date], the answer is X."
    
  2. Running one vague query and declaring the search complete — always build at least Primary + Precision + Expansion variants.

  3. Ignoring time-sensitivity — searching "latest Go version" without after: gives you results from 2019. Technical topics go stale fast.

    BAD: Go latest features
    GOOD: Go 1.24 new features after:2025-01-01
    
  4. Returning raw links without synthesis — the user wants an answer, not a link dump. Synthesize first, then provide sources and reusable queries.

  5. Using Google for topics better served by platform-specific search — WeChat articles, Xiaohongshu reviews, and Douyin content are not well-indexed by Google. Tell the user which platform to search directly.

  6. Verifying an AI-generated claim with another AI tool — use Google to find original sources. Do not verify AI with AI.

  7. Searching indefinitely without stopping — respect the query budget. 8 queries without a satisfactory answer means the problem is framing, not insufficient searching.

  8. Omitting confidence and source-tier labels on key numbers — every key numeric claim must carry both labels. If you cannot label it, do not present it as settled.

Honest Degradation

When search results are insufficient, degrade explicitly:

LevelConditionAction
FullStrong primary source directly answers the questionProvide direct conclusion with full evidence
PartialOnly derivative or stale sources availableProvide qualified answer + what remains uncertain + next search strategy
BlockedNo relevant results after budget exhaustion, or content is behind paywall/walled gardenState explicitly what was not found + recommend platform-specific search or AI synthesis tool

Decision tree:

Is your strongest source official/primary AND directly answers the question?
  → YES → Full
  → NO  → Is the best source derivative, stale, or from a competing vendor?
           → YES → Partial (state what remains uncertain + next search strategy)
           → NO  → Did you exhaust the query budget without relevant results?
                    → YES → Blocked (state what was not found + platform/tool recommendation)

Never guess to fill gaps. State uncertainty clearly.

Safety Rules

  1. For public-information lookups, use public sources only and separate fact from inference.
  2. Never present identity linkage (two records = same person) as confirmed unless sources make it explicit.
  3. When sources conflict, explain the conflict rather than picking a side silently.
  4. For high-conflict topics, follow the full protocol in references/high-conflict-topics.md.
  5. Every key numeric claim must carry both a confidence label and a source-tier label.
  6. If the evidence is weak, say so and provide the next search strategy instead of guessing.

Output Contract

Every completed use of this skill must include the fields below. Fields are graded MUST / SHOULD / MAY per mode:

#FieldQuickStandardDeep
1Execution mode — Quick / Standard / DeepMUSTMUSTMUST
2Degradation level — Full / Partial / BlockedMUSTMUSTMUST
3Conclusion summary — answer directly, state exact dates, distinguish fact/inference/unknownMUSTMUSTMUST
4Evidence chain status — which links satisfied, which missingMAYMUSTMUST
5Key evidence — strongest sources, what each contributed, cross-check sourceMAYMUSTMUST
6Source assessment — credibility, gaps, stale dates, disagreements, confidence justificationMAYSHOULDMUST
7Key numbersvalue + date + confidence (High/Medium/Low) + source tier (Official/Primary/Third-party/OSINT/Adversary)MUST (if numbers exist)MUSTMUST
8Reusable queries — copyable Google queries with precision + expansion variantsMUST (≥2)MUST (≥3)MUST (≥5)
9Gate execution log — one-line summary per gate (skip for Quick, recommended for Standard/Deep)SKIPSHOULDSHOULD

Load References Selectively

For every search task, before building queries: → Load references/query-patterns.md for core query construction patterns (Primary / Precision / Expansion variants), category-specific operators, and one-variable-at-a-time refinement strategy.

When the search category is Programmer search (error debugging, API docs, code examples, benchmarks, RFC lookup): → Load references/programmer-search-patterns.md for error message normalization, site: operator shortcuts per source type (GitHub, Stack Overflow, official docs), and technical evidence quality criteria.

When evaluating whether sources are strong enough to support a claim, or when sources conflict: → Load references/source-evaluation.md for the source ranking table (Official > Academic > Authoritative secondary > …), conflict resolution rules, originality / recency / directness / independence scoring criteria.

When the topic is Chinese-language or China-centric (content lives in Baidu, Zhihu, WeChat, Weibo): → Load references/chinese-search-ecosystem.md for content-type-to-source mapping, Chinese-specific search operators, and cross-validation rules for Chinese-only sources.

When the topic involves active conflict, elections, disasters, market moves, or any fast-changing event: → Load references/high-conflict-topics.md for stricter scope-locking rules, source-tiering requirements (no single outlet, require independent confirmation), and temporal anchoring conventions.

When assessing whether to stop searching or escalate to a different tool (AI search, database query): → Load references/ai-search-and-termination.md for budget exhaustion thresholds, escalation signals (no new evidence after N queries), and AI-search-vs-Google decision criteria.

When calibrating output quality or validating the report format for the first time: → Load references/worked-examples.md for fully worked examples across Quick / Standard / Deep modes with complete output contract fields, evidence chain notation, and reusable query formatting.

Worked Examples (Skeleton)

Full worked examples with complete Output Contract fields: read references/worked-examples.md.

Example 1: Quick mode

"sync.Pool GC 回收?" → Gates pass → Evidence chain: 1 official source → 2 queries (site:go.dev) → Full degradation → answer with High + Official labels + 2 reusable queries.

Example 2: Standard mode

"MySQL 连接池配置" → Gates pass → Evidence chain: 1 official + 1 practitioner → 4/5 queries (EN + CN) → Full degradation → formula + pitfalls with Medium-High + Mixed official + practitioner labels + gate execution log.