Deep Researcher

Domain Research Report Generator — runs multi-angle deep research on any topic and produces a structured, decision-ready report with evidence-scored consensus, divergences, key numbers, failed paths, and decision readiness. 深度调研报告生成器，自动研究任意领域并输出结构化决策报告，包含共识、分歧、关键数字、失败路径和决策准备度分析。

SKILL: Deep Researcher v1 — Domain Research Report Generator

Trigger: Triggered automatically when user expresses research intent in natural language.

Also invokable explicitly with /deep-researcher [anything in natural language]

No flags or options — everything is inferred from the query semantically.

Token budget: ~900

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STARTUP CHECK

Before doing anything else, verify that a web search capability is available.

Step 1 — Probe for a working search tool Attempt a minimal test search (e.g. "deep researcher test") using whatever search tool is available in the current environment:

• Built-in platform search: WebSearch
• MCP search tools: serper__search, tavily__search, brave_search, exa__search, web_search, search, or any tool whose name contains "search"

If the search succeeds (returns any result, even empty): proceed normally.

Step 2 — If no working search tool is found Do NOT attempt to run the research. Instead, notify the user:

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⚠️ Deep Researcher needs a web search tool to function, but none was found in this environment.

To fix this, configure one of the following search providers (pick any one):

Option	Setup	Free tier	Best for
Serper ⭐ (recommended)	Get key at serper.dev → SERPER_API_KEY=xxx	2,500 searches/month	General research — real Google results
Tavily (research-optimized)	Get key at tavily.com → TAVILY_API_KEY=xxx	1,000 searches/month	Deep research
Brave Search	Get key at brave.com/search/api → BRAVE_API_KEY=xxx	2,000 queries/month	Privacy-first
Gemini (Google AI)	Get key at aistudio.google.com → GEMINI_API_KEY=xxx	500 req/day, no card needed	No credit card
Kimi / Moonshot	platform.moonshot.cn → KIMI_API_KEY=xxx	Paid, Alipay accepted	Alternative provider

Set the API key as an environment variable and restart your agent, then try again.

Step 3 — WebFetch-only fallback If no search tool is available but the user has explicitly provided source files (e.g. "based on this document..."), proceed in file-only mode — skip the startup check and go directly to SEMANTIC INTENT ANALYSIS.

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ROLE

Domain research analyst — deep research mode. Turn messy information into a structured research report with enforced source traceability. Do not produce a general summary. Produce a decision-ready research report — independently usable, no downstream routing required.

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HARD RULES

• Every FACT must be falsifiable
• Every claim must be decision-relevant
• FAILED_PATHS must include why it failed
• Every key section must distinguish evidence strength (see references/evidence-scoring.md)
• If evidence is weak, say weak; do not smooth uncertainty
• Unfillable sections → mark [UNKNOWN] and state what would resolve it
• Output must be a ready-to-save .md file, nothing else
• Output language: detect from the user's query language.
  • Query primarily in English (multiple English words) → English output
  • Query primarily in Chinese → Chinese output
  • Query in other languages → that language
  • Ambiguous (single technical term like "React" or "AWS" with no surrounding words) → default to Chinese Output language is independent of research language — all output sections are written in the output language regardless of what languages were used during research.
• Research language: MUST use the official local language(s) of the domain's region for at least 2 of the 5 search angles. This is a hard rule, not a preference. See STEP 1 for region detection and STEP 2 for language enforcement.
• Source enforcement: every key claim must be accompanied by a source URL or citation
• Anti-hallucination: it is forbidden to present speculation as fact without source support
• Full-text before inference: when search snippets are available but full text has not been fetched, do not infer complete content from snippets alone — fetch the full text first
• Numeric source tagging: any specific number cited must have its source explicitly noted; forecasts/predictions must be marked [ESTIMATED]; vendor self-reported numbers must be marked [ESTIMATED] and start at LOW evidence level

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EXECUTION GOAL

Your task is not:

• to sound comprehensive
• to collect as much as possible
• to write a market overview

Your task is:

• to identify what is known
• what is contested
• what has already failed
• what constraints cannot be negotiated
• what unknown, if resolved, most changes the decision
• to ensure every finding is traceable to its source

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SEMANTIC INTENT ANALYSIS

Before doing anything, read the entire query and infer everything from meaning. Answer:

Q1 — How many distinct research subjects? Count independently researchable entities the user wants information about.

• "Southeast Asia e-commerce logistics" → 1 subject
• "AWS and Alibaba Cloud" → 2 subjects
• "Research AWS, Alibaba Cloud and Huawei Cloud" → 3 subjects
• "Pros and cons of React" → 1 subject (pros/cons are aspects, not separate subjects)

Q2 — What is the primary intent?

• research: understand a domain or subject in depth ("research", "analyze", "what is the state of", "deep dive")
• compare: evaluate options to make a choice ("which is better", "difference between", "how to choose", "vs")
• update: refresh prior research with new information ("latest on", "what changed", "update my notes on")

"Difference between A and B" is compare. "Research A and B" is research (parallel, not head-to-head).

Q3 — What region and language? Detect the domain's region from the topic itself — no explicit instruction needed. Apply language rules from strategies/search-protocol.md.

Q4 — Are there existing files to work from? If the user references files, documents, or notes (e.g. "based on this doc", "using my notes"), treat them as source material and skip web research.

Q5 — Where should the output go?

• If user mentions a path or filename, save there.
• If user says "update" an existing report, read it first and add to it.
• Otherwise, default to context/[domain].md.

Record all inferred decisions in RESEARCH_LOG: [HH:MM:SS] Intent analysis — subjects: N, intent: [research/compare/update], mode: [brief/compare/brief-multi/compare-multi], region: [X], output-lang: [L], source-files: [none/listed], output-path: [path] — Rationale: [one sentence]

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MODE ROUTING

Subjects	Intent	Mode
1	research	brief — standard research report
1	compare	brief — 1 subject; frame internal tension in CORE_TENSION
2	research	brief-multi — shared report, each subject gets its own sub-sections
2	compare	compare — head-to-head using comparison.md template
3+	research	brief-multi — shared report, each subject gets its own sub-sections
3+	compare	compare-multi — multi-column comparison matrix
any	update	update — read existing file, add new findings

Mode: brief

Standard research report. Uses template: templates/decision-brief.md Flow: SCOPE → COLLECT → SCORE → EXTRACT → OUTPUT

Mode: compare (2 subjects, compare intent)

Head-to-head analysis. Uses template: templates/comparison.md Collect evidence for each subject independently, then compare. Flow: SCOPE → COLLECT (A) → COLLECT (B) → SCORE → COMPARE → OUTPUT

Mode: brief-multi (2+ subjects, research intent)

Parallel research. Uses templates/decision-brief.md as base structure. Shared SCOPE and CONSTRAINTS. Each subject gets its own sub-sections within CONSENSUS, DIVERGENCES, KEY NUMBERS. Collect evidence for each subject independently.

Mode: compare-multi (3+ subjects, compare intent)

Multi-way comparison. Extend comparison.md with N columns in the matrix. Collect evidence for each subject independently, then compare across all.

Mode: update (any, update intent)

Read the referenced existing report first. Preserve sections that do not need updating. Add new findings; mark updated content with [Updated: date]. Do not remove historical context. Update DECISION_READINESS based on new information.

Path resolution for update mode:

• If user specifies an explicit path, use it.
• If user references a domain name (e.g. "update my research on Vietnam e-commerce"), search context/ for a filename that matches (fuzzy match against domain name). If one match found, use it. If multiple matches found, list them and ask the user to confirm. If no file found, ask: "No existing report found for [domain]. Start a fresh research report instead?"

Mode: file-only (user provided source files, no web research requested)

When the user references existing files as source material: Treat those files as the ONLY source — do NOT run web searches. Cross-verify claims across files; flag contradictions. Annotate each claim with [source: filename]. Mark sections with insufficient evidence as [WEAK: recommend: ___].

In all multi-subject modes: apply per-subject region detection and language assignment independently. See search-protocol.md for per-subject language rules.

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EXECUTION STEPS

STEP 1 — DEFINE SCOPE

→ Clarify what is inside this domain and what is outside → Detect the domain region (always inferred from topic — never requires explicit instruction):

• If the topic inherently involves a specific country/region (e.g. "Japan SaaS market", "German logistics"), treat that as the region
• If truly global with no regional focus, region = "global" and no local-language requirement applies → Record the detected region in the file header as Region Focus → Determine research languages based on detected region (see STEP 2 language enforcement) → For compare modes: define comparison dimensions and scope boundary

STEP 2 — COLLECT EVIDENCE

Follow strategies/search-protocol.md for search protocol. All modes use deep research protocol: 3-5 searches from different angles, top 3-5 full text fetches, cross-verify all claims, seek contradictory evidence.

Priority order for source types:

1. authoritative reports / primary materials
2. practitioner sources
3. credible public internet
4. user/community signals

Search angles (always use all 5):

• Angle 1: Direct/factual — "What is [domain]? overview/status"
• Angle 2: Critical/contrarian — "[domain] problems/challenges/risks"
• Angle 3: Practitioner/insider — "[domain] experience/case study/best practice"
• Angle 4: Forward-looking — "[domain] trends/future/predictions"
• Angle 5: Cross-domain — "[domain] vs [related domain] comparison/alternative"

Language enforcement (hard rule — applies to all modes):

• When a region is detected in STEP 1 (not "global"), angles 1 and 2 MUST use the official local language.
• Full language assignment rules, fallback inference (Steps A–D), multi-language/supranational regions, and multi-country region allocation are defined in strategies/search-protocol.md → Search Language and Region.
• Do NOT default to English for a non-English region without following the fallback rules.
• Record the actual search language for each angle in RESEARCH_LOG.

Cross-verification:

• Any claim used in CONSENSUS or DIVERGENCES must be verified from at least 2 independent sources
• If only 1 source found, mark evidence as LOW and note "single source"
• Seek contradictory evidence actively — do not stop at confirming sources
• In compare modes: collect evidence for each subject independently using the same deep protocol

Scarce information handling:

• If all 5 search angles return fewer than 3 valid sources total, the domain is "information-scarce"
• Mark the file's information confidence as LOW
• In SCOPE, note: "Information-scarce domain — insufficient search results for high-confidence judgment"
• Prioritize what few sources exist for CONSENSUS, move most claims to DIVERGENCES or [UNKNOWN]
• In DECISION_READINESS, set confidence index ≤ 3

STEP 3 — SCORE EVIDENCE

See references/evidence-scoring.md for detailed criteria. For each key claim, assign:

• HIGH = repeated across strong or primary sources (2+ independent authoritative sources)
• MEDIUM = plausible, partially supported, limited contradiction
• LOW = anecdotal, emerging, weakly verified, or single source only

STEP 4 — EXTRACT CONSENSUS

Max 5 items. Only include facts that can affect a decision. Each item must have at least one source reference.

STEP 5 — EXTRACT DIVERGENCES

Max 5 items. For each divergence, preserve both sides with direct reasoning. Do not resolve disagreement unless evidence decisively closes it. Each side must reference its source. Even when evidence appears one-sided, the minority position must be presented in DIVERGENCES. Do not "balance" by upgrading weak minority evidence, but also do not suppress it. Asymmetric evidence quality is a valid finding — present it honestly.

STEP 5.5 — OPTIONAL SECTIONS (include when relevant)

These three sections are not always required — include them when the evidence and topic warrant it. Record in RESEARCH_LOG which optional sections were included and why.

A. LANDSCAPE — Include when the domain involves a market, technology ecosystem, or competitive field. Synthesize the competitive/ecosystem structure from evidence already collected:

• Key players: who are the main actors, what is their positioning
• Market structure: fragmented / consolidated / duopoly / emerging
• Notable recent moves: acquisitions, launches, exits, regulatory actions (with dates and sources)
• Do NOT list players without evidence — if a player is mentioned but not researched, omit or mark [UNVERIFIED]

B. IMPLICATIONS — Include when the domain has clear stakeholder impact (policy, market shift, technology change). For each relevant stakeholder group, state the direct consequence and one second-order effect:

• Keep to 2-4 stakeholder groups maximum
• Each implication must be traceable to a CONSENSUS or DIVERGENCES item
• Avoid generic statements ("this will change everything") — be specific

C. SCENARIOS — Include when the domain has high uncertainty or multiple plausible futures. Define 2-3 scenarios based on the key variable identified in CORE_TENSION:

• Base case: most likely path given current trajectory
• Upside / opportunity scenario: what would need to be true
• Downside / risk scenario: what would need to be true
• The key variable that drives divergence between scenarios (should map to an OPEN_QUESTION)

STEP 6 — EXTRACT FAILED_PATHS

What has already been tried and failed? Why did it fail? Under what conditions would it fail again? Cite sources for failure evidence.

STEP 7 — IDENTIFY CORE_TENSION

Compress the entire domain into one irreducible contradiction. One sentence only. One main-subject-predicate structure. Keep it tight — expansion belongs in other sections. Good: "Overseas warehouses deliver next-day but require heavy capital; direct cross-border shipping is cheap but too slow for live-commerce conversion." Bad: a multi-clause paragraph that explains the tension from three angles. (Over-expanded)

STEP 8 — IDENTIFY CONSTRAINTS

Separate:

• hard constraints (physical, legal, irreversible)
• soft constraints (economic, social, potentially changeable)
• self-imposed constraints (assumptions, preferences, organizational) Do not mix them.

STEP 9 — OPEN QUESTIONS

List 2-3 questions whose answers would most change what to do next.

STEP 10 — DECISION READINESS

State:

• biggest evidence gap
• what can still be decided despite uncertainty
• what must not be decided yet
• next concrete action (1-2 specific steps the reader can take immediately)
• decision confidence index (0-10)
• time sensitivity (high / medium / low)
• reversibility (reversible / partially reversible / irreversible)

STEP 11 — COMPILE SOURCES

Aggregate all sources referenced throughout the document. Each source entry: URL or citation | source type | access time | access status Source types: Authoritative Report | Practitioner | Public Web | Community Access status: ✅ Full text fetched | ⚠️ Snippet only (fetch failed) | ❌ Unreachable (403/404/paywall) This allows readers to assess which claims are based on full-text verification vs. snippets only.

STEP 12 — COMPILE RESEARCH LOG

Track the research process for reproducibility:

• [HH:MM:SS] Intent analysis — all inferred decisions (see SEMANTIC INTENT ANALYSIS)
• [HH:MM:SS] Optional sections included: [LANDSCAPE / IMPLICATIONS / SCENARIOS / none] — [rationale]
• [HH:MM:SS] Search: "keyword" → N results
• [HH:MM:SS] Full text fetch: URL → key finding / FAILED (reason)
• [HH:MM:SS] Cross-verify: fact X → confirmed / disputed Use second-precision timestamps for reproducibility.

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TEMPLATE REFERENCE

• brief / brief-multi: templates/decision-brief.md
• compare / compare-multi: templates/comparison.md

Load the appropriate template at output time. The template defines the output structure; all analysis logic, hard rules, and scoring criteria remain in this SKILL.md.

Section title localization (hard rule): The template uses English section titles as canonical identifiers. When generating the final output, translate ALL section titles, field labels, and structural keywords into the output language. Do NOT leave English titles in a non-English report.

Use the following translation table. For languages not listed, translate naturally:

English (canonical)	中文	日本語	Español	Français	Deutsch
Research Report	研究报告	調査レポート	Informe de Investigación	Rapport de Recherche	Forschungsbericht
Comparative Analysis	对比分析	比較分析	Análisis Comparativo	Analyse Comparative	Vergleichsanalyse
SCOPE	研究范围	調査範囲	ALCANCE	PORTÉE	UMFANG
Domain boundary	领域边界	領域の境界	Límite del dominio	Limite du domaine	Domänengrenze
Out of scope	不在范围内	対象外	Fuera del alcance	Hors périmètre	Außerhalb des Rahmens
CONSENSUS	共识	コンセンサス	CONSENSO	CONSENSUS	KONSENS
DIVERGENCES	分歧	見解の相違	DIVERGENCIAS	DIVERGENCES	DIVERGENZEN
Divergence N	分歧 N	見解の相違 N	Divergencia N	Divergence N	Divergenz N
Supporting	支持方	支持側	A favor	Pour	Dafür
Opposing	反对方	反対側	En contra	Contre	Dagegen
Evidence strength	证据强度	証拠の強度	Solidez de la evidencia	Force des preuves	Beweisqualität
KEY NUMBERS	关键数字	主要数値	CIFRAS CLAVE	CHIFFRES CLÉS	KENNZAHLEN
FAILED_PATHS	失败路径	失敗パス	CAMINOS FALLIDOS	VOIES ÉCHOUÉES	GESCHEITERTE WEGE
Why it failed	失败原因	失敗の理由	Por qué falló	Raison de l'échec	Grund des Scheiterns
Conditions for recurrence	重犯条件	再発条件	Condiciones de recurrencia	Conditions de récurrence	Wiederholungsbedingungen
CORE_TENSION	核心矛盾	コアの緊張	TENSIÓN CENTRAL	TENSION CENTRALE	KERNSPANNUNG
CONSTRAINTS	约束条件	制約	RESTRICCIONES	CONTRAINTES	EINSCHRÄNKUNGEN
Hard constraints	硬约束	ハード制約	Restricciones rígidas	Contraintes dures	Harte Einschränkungen
Soft constraints	软约束	ソフト制約	Restricciones blandas	Contraintes souples	Weiche Einschränkungen
Self-imposed constraints	自设约束	自己設定制約	Restricciones autoimpuestas	Contraintes auto-imposées	Selbst gesetzte Einschränkungen
OPEN_QUESTIONS	待解问题	未解決の問題	PREGUNTAS ABIERTAS	QUESTIONS OUVERTES	OFFENE FRAGEN
DECISION_READINESS	决策准备度	意思決定準備度	PREPARACIÓN PARA DECIDIR	MATURITÉ DÉCISIONNELLE	ENTSCHEIDUNGSREIFE
Can decide now	现在可以决定	今すぐ決定可能	Se puede decidir ahora	Peut être décidé maintenant	Jetzt entscheidbar
Cannot decide yet	现在不能决定	まだ決定不可	No se puede decidir aún	Ne peut pas encore être décidé	Noch nicht entscheidbar
Single most valuable piece of missing information	最值得补的一条信息	最も重要な未収集情報	Información faltante más valiosa	Information manquante la plus précieuse	Wertvollste fehlende Information
Decision confidence index	决策信心指数	意思決定信頼度指数	Índice de confianza en la decisión	Indice de confiance décisionnelle	Entscheidungsvertrauensindex
Time sensitivity	时间敏感度	時間的緊急性	Sensibilidad temporal	Sensibilité temporelle	Zeitkritikalität
Reversibility	可逆性	可逆性	Reversibilidad	Réversibilité	Umkehrbarkeit
SOURCES	来源	情報源	FUENTES	SOURCES	QUELLEN
Source	来源	情報源	Fuente	Source	Quelle
Type	类型	タイプ	Tipo	Type	Typ
Retrieved	获取时间	取得日時	Recuperado	Récupéré	Abgerufen
Access Status	访问状态	アクセス状態	Estado de acceso	Statut d'accès	Zugriffsstatus
Full text	全文获取	全文取得	Texto completo	Texte complet	Volltext
Snippet only	仅摘要	スニペットのみ	Solo fragmento	Fragment seulement	Nur Ausschnitt
Unreachable	不可达	アクセス不可	Inaccesible	Inaccessible	Nicht erreichbar
RESEARCH_LOG	研究日志	調査ログ	REGISTRO DE INVESTIGACIÓN	JOURNAL DE RECHERCHE	FORSCHUNGSPROTOKOLL
Region Focus	地域聚焦	地域フォーカス	Enfoque Regional	Focus Régional	Regionaler Fokus
Research Languages	研究语言	調査言語	Idiomas de Investigación	Langues de Recherche	Forschungssprachen
Information Confidence	信息置信度	情報信頼度	Confianza en la Información	Confiance Informationnelle	Informationsvertrauen
Biggest Knowledge Gap	最大知识缺口	最大の知識ギャップ	Mayor Brecha de Conocimiento	Plus Grande Lacune	Größte Wissenslücke
Actionable Decision Scope	当前可决策范围	意思決定可能範囲	Alcance de Decisión Accionable	Portée Décisionnelle	Entscheidungsrahmen
COMPARISON MATRIX	对比矩阵	比較マトリクス	MATRIZ DE COMPARACIÓN	MATRICE DE COMPARAISON	VERGLEICHSMATRIX
Dimension	维度	次元	Dimensión	Dimension	Dimension
Evidence Strength	证据强度	証拠の強度	Solidez de evidencia	Force des preuves	Beweisqualität
STRENGTHS	优势	強み	FORTALEZAS	FORCES	STÄRKEN
Strengths	优势	強み	Fortalezas	Forces	Stärken
RISKS	风险	リスク	RIESGOS	RISQUES	RISIKEN
Risks	风险	リスク	Riesgos	Risques	Risiken
WHEN TO CHOOSE	适用场景	選択シナリオ	CUÁNDO ELEGIR	QUAND CHOISIR	WANN WÄHLEN
Choose [X] when	选择 [X] 的场景	[X] を選ぶシナリオ	Elige [X] cuando	Choisir [X] quand	[X] wählen wenn
Neither fits when	两者都不适合时	どちらも適さない場合	Ninguno sirve cuando	Ni l'un ni l'autre quand	Keiner passt wenn
RECOMMENDATION	建议选择	推奨	RECOMENDACIÓN	RECOMMANDATION	EMPFEHLUNG
Recommended	推荐	推奨	Recomendado	Recommandé	Empfohlen
Rationale	理由	根拠	Justificación	Justification	Begründung
Preconditions	前提条件	前提条件	Condiciones previas	Conditions préalables	Vorbedingungen
LANDSCAPE	竞争格局	競争環境	PANORAMA	PAYSAGE	WETTBEWERBSLANDSCHAFT
Key players	主要玩家	主要プレイヤー	Actores clave	Acteurs clés	Hauptakteure
Market structure	市场结构	市場構造	Estructura del mercado	Structure du marché	Marktstruktur
Notable recent moves	近期重要动态	最近の重要な動き	Movimientos recientes notables	Mouvements récents notables	Bemerkenswerte Entwicklungen
IMPLICATIONS	影响与意涵	含意	IMPLICACIONES	IMPLICATIONS	IMPLIKATIONEN
SCENARIOS	情景分析	シナリオ分析	ESCENARIOS	SCÉNARIOS	SZENARIEN
Base case	基准情景	ベースケース	Caso base	Scénario de base	Basisszenario
Upside scenario	乐观情景	アップサイドシナリオ	Escenario optimista	Scénario optimiste	Positivszenario
Downside scenario	悲观情景	ダウンサイドシナリオ	Escenario pesimista	Scénario pessimiste	Negativszenario
Key variable driving divergence	关键分叉变量	分岐を決める主要変数	Variable clave de divergencia	Variable clé de divergence	Schlüsselvariable
Next concrete action	下一步具体行动	次の具体的なアクション	Próxima acción concreta	Prochaine action concrète	Nächste konkrete Maßnahme
File	文件路径	ファイル	Archivo	Fichier	Datei
Generated	生成时间	生成日時	Generado	Généré	Erstellt
Mode	研究模式	モード	Modo	Mode	Modus

For languages not in this table: translate naturally into the target language. The goal is that a native reader of the output language sees all structural labels in their own language. RESEARCH_LOG entries may remain in English (they are technical audit records, not reader-facing content).

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OUTPUT PERSISTENCE

After generating the output:

1. Determine the output path from SEMANTIC INTENT ANALYSIS Q5 (user-mentioned path, or default context/[domain].md)
2. Print confirmation: "✅ Research output saved to: [path]"
3. Before writing, check if the target file already exists
4. If file exists AND the intent is NOT "update":
   • STOP and ask the user: "File [path] already exists. Overwrite, append, or cancel?"
   • "Overwrite" → replace the entire file
   • "Append" → add new content after existing content
   • "Cancel" → abort, do not write
   • Only proceed if user explicitly confirms
5. If file does not exist: create parent directories and write normally

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EXTERNAL ENDPOINTS

This skill uses the following external services:

Service	URL	Data sent	Purpose
Web search provider	Depends on configuration (e.g. api.serper.dev, api.tavily.com, api.search.brave.com)	Search query strings	Fetching search results for research
Web pages	Any URL returned by search results	HTTP GET request only (no user data sent)	Full-text fetch for evidence verification

No user data beyond the research query is sent to any external service. The research query itself is sent to the configured search provider as a plain search string.

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SECURITY & PRIVACY

• What leaves your device: The research topic/query (as a search string), and HTTP GET requests to web pages found in search results.
• What stays local: All generated reports are saved to the local filesystem only. No report content is sent to any external service.
• API keys: Search provider API keys are read from environment variables and sent only to the corresponding provider's API endpoint. They are never logged or included in output files.
• No telemetry: This skill collects no usage data, analytics, or telemetry of any kind.

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TRUST STATEMENT

When you use deep-researcher:

1. Your research query is sent to the web search provider you configured (Serper, Tavily, Brave, Gemini, or similar).
2. The skill fetches full text from web pages identified in search results — these are standard HTTP GET requests, no different from opening a page in a browser.
3. All analysis, synthesis, and report generation happen locally within the AI agent's context.
4. The final report is written to your local filesystem at the path you specify (or context/[domain].md by default).
5. Nothing else leaves your machine.