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https://github.com/azaion/gps-denied-onboard.git
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Update README to reflect changes in test infrastructure organization and task decomposition workflow. Remove obsolete E2E test templates and clarify input specifications for integration tests. Enhance documentation for planning and implementation phases, including new directory structures and task management processes.
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# Comparison & Analysis Frameworks — Reference
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## General Dimensions (select as needed)
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1. Goal / What problem does it solve
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2. Working mechanism / Process
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3. Input / Output / Boundaries
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4. Advantages / Disadvantages / Trade-offs
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5. Applicable scenarios / Boundary conditions
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6. Cost / Benefit / Risk
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7. Historical evolution / Future trends
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8. Security / Permissions / Controllability
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## Concept Comparison Specific Dimensions
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1. Definition & essence
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2. Trigger / invocation method
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3. Execution agent
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4. Input/output & type constraints
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5. Determinism & repeatability
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6. Resource & context management
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7. Composition & reuse patterns
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8. Security boundaries & permission control
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## Decision Support Specific Dimensions
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1. Solution overview
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2. Implementation cost
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3. Maintenance cost
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4. Risk assessment
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5. Expected benefit
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6. Applicable scenarios
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7. Team capability requirements
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8. Migration difficulty
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# Novelty Sensitivity Assessment — Reference
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## Novelty Sensitivity Classification
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| Sensitivity Level | Typical Domains | Source Time Window | Description |
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|-------------------|-----------------|-------------------|-------------|
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| **Critical** | AI/LLMs, blockchain, cryptocurrency | 3-6 months | Technology iterates extremely fast; info from months ago may be completely outdated |
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| **High** | Cloud services, frontend frameworks, API interfaces | 6-12 months | Frequent version updates; must confirm current version |
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| **Medium** | Programming languages, databases, operating systems | 1-2 years | Relatively stable but still evolving |
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| **Low** | Algorithm fundamentals, design patterns, theoretical concepts | No limit | Core principles change slowly |
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## Critical Sensitivity Domain Special Rules
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When the research topic involves the following domains, special rules must be enforced:
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**Trigger word identification**:
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- AI-related: LLM, GPT, Claude, Gemini, AI Agent, RAG, vector database, prompt engineering
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- Cloud-native: Kubernetes new versions, Serverless, container runtimes
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- Cutting-edge tech: Web3, quantum computing, AR/VR
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**Mandatory rules**:
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1. **Search with time constraints**:
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- Use `time_range: "month"` or `time_range: "week"` to limit search results
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- Prefer `start_date: "YYYY-MM-DD"` set to within the last 3 months
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2. **Elevate official source priority**:
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- Must first consult official documentation, official blogs, official Changelogs
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- GitHub Release Notes, official X/Twitter announcements
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- Academic papers (arXiv and other preprint platforms)
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3. **Mandatory version number annotation**:
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- Any technical description must annotate the current version number
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- Example: "Claude 3.5 Sonnet (claude-3-5-sonnet-20241022) supports..."
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- Prohibit vague statements like "the latest version supports..."
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4. **Outdated information handling**:
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- Technical blogs/tutorials older than 6 months -> historical reference only, cannot serve as factual evidence
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- Version inconsistency found -> must verify current version before using
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- Obviously outdated descriptions (e.g., "will support in the future" but now already supported) -> discard directly
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5. **Cross-validation**:
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- Highly sensitive information must be confirmed from at least 2 independent sources
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- Priority: Official docs > Official blogs > Authoritative tech media > Personal blogs
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6. **Official download/release page direct verification (BLOCKING)**:
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- Must directly visit official download pages to verify platform support (don't rely on search engine caches)
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- Use `WebFetch` to directly extract download page content
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- Search results about "coming soon" or "planned support" may be outdated; must verify in real time
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- Platform support is frequently changing information; cannot infer from old sources
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7. **Product-specific protocol/feature name search (BLOCKING)**:
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- Beyond searching the product name, must additionally search protocol/standard names the product supports
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- Common protocols/standards to search:
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- AI tools: MCP, ACP (Agent Client Protocol), LSP, DAP
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- Cloud services: OAuth, OIDC, SAML
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- Data exchange: GraphQL, gRPC, REST
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- Search format: `"<product_name> <protocol_name> support"` or `"<product_name> <protocol_name> integration"`
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## Timeliness Assessment Output Template
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```markdown
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## Timeliness Sensitivity Assessment
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- **Research Topic**: [topic]
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- **Sensitivity Level**: Critical / High / Medium / Low
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- **Rationale**: [why this level]
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- **Source Time Window**: [X months/years]
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- **Priority official sources to consult**:
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1. [Official source 1]
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2. [Official source 2]
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- **Key version information to verify**:
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- [Product/technology 1]: Current version ____
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- [Product/technology 2]: Current version ____
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```
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# Quality Checklists — Reference
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## General Quality
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- [ ] All core conclusions have L1/L2 tier factual support
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- [ ] No use of vague words like "possibly", "probably" without annotating uncertainty
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- [ ] Comparison dimensions are complete with no key differences missed
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- [ ] At least one real use case validates conclusions
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- [ ] References are complete with accessible links
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- [ ] Every citation can be directly verified by the user (source verifiability)
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- [ ] Structure hierarchy is clear; executives can quickly locate information
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## Mode A Specific
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- [ ] Phase 1 completed: AC assessment was presented to and confirmed by user
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- [ ] AC assessment consistent: Solution draft respects the (possibly adjusted) acceptance criteria and restrictions
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- [ ] Competitor analysis included: Existing solutions were researched
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- [ ] All components have comparison tables: Each component lists alternatives with tools, advantages, limitations, security, cost
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- [ ] Tools/libraries verified: Suggested tools actually exist and work as described
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- [ ] Testing strategy covers AC: Tests map to acceptance criteria
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- [ ] Tech stack documented (if Phase 3 ran): `tech_stack.md` has evaluation tables, risk assessment, and learning requirements
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- [ ] Security analysis documented (if Phase 4 ran): `security_analysis.md` has threat model and per-component controls
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## Mode B Specific
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- [ ] Findings table complete: All identified weak points documented with solutions
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- [ ] Weak point categories covered: Functional, security, and performance assessed
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- [ ] New draft is self-contained: Written as if from scratch, no "updated" markers
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- [ ] Performance column included: Mode B comparison tables include performance characteristics
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- [ ] Previous draft issues addressed: Every finding in the table is resolved in the new draft
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## Timeliness Check (High-Sensitivity Domain BLOCKING)
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When the research topic has Critical or High sensitivity level:
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- [ ] Timeliness sensitivity assessment completed: `00_question_decomposition.md` contains a timeliness assessment section
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- [ ] Source timeliness annotated: Every source has publication date, timeliness status, version info
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- [ ] No outdated sources used as factual evidence (Critical: within 6 months; High: within 1 year)
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- [ ] Version numbers explicitly annotated for all technical products/APIs/SDKs
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- [ ] Official sources prioritized: Core conclusions have support from official documentation/blogs
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- [ ] Cross-validation completed: Key technical information confirmed from at least 2 independent sources
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- [ ] Download page directly verified: Platform support info comes from real-time extraction of official download pages
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- [ ] Protocol/feature names searched: Searched for product-supported protocol names (MCP, ACP, etc.)
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- [ ] GitHub Issues mined: Reviewed product's GitHub Issues popular discussions
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- [ ] Community hotspots identified: Identified and recorded feature points users care most about
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## Target Audience Consistency Check (BLOCKING)
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- [ ] Research boundary clearly defined: `00_question_decomposition.md` has clear population/geography/timeframe/level boundaries
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- [ ] Every source has target audience annotated in `01_source_registry.md`
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- [ ] Mismatched sources properly handled (excluded, annotated, or marked reference-only)
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- [ ] No audience confusion in fact cards: Every fact has target audience consistent with research boundary
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- [ ] No audience confusion in the report: Policies/research/data cited have consistent target audiences
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## Source Verifiability
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- [ ] All cited links are publicly accessible (annotate `[login required]` if not)
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- [ ] Citations include exact section/page/timestamp for long documents
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- [ ] Cited facts have corresponding statements in the original text (no over-interpretation)
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- [ ] Source publication/update dates annotated; technical docs include version numbers
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- [ ] Unverifiable information annotated `[limited source]` and not sole support for core conclusions
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# Source Tiering & Authority Anchoring — Reference
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## Source Tiers
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| Tier | Source Type | Purpose | Credibility |
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|------|------------|---------|-------------|
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| **L1** | Official docs, papers, specs, RFCs | Definitions, mechanisms, verifiable facts | High |
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| **L2** | Official blogs, tech talks, white papers | Design intent, architectural thinking | High |
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| **L3** | Authoritative media, expert commentary, tutorials | Supplementary intuition, case studies | Medium |
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| **L4** | Community discussions, personal blogs, forums | Discover blind spots, validate understanding | Low |
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## L4 Community Source Specifics (mandatory for product comparison research)
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| Source Type | Access Method | Value |
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|------------|---------------|-------|
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| **GitHub Issues** | Visit `github.com/<org>/<repo>/issues` | Real user pain points, feature requests, bug reports |
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| **GitHub Discussions** | Visit `github.com/<org>/<repo>/discussions` | Feature discussions, usage insights, community consensus |
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| **Reddit** | Search `site:reddit.com "<product_name>"` | Authentic user reviews, comparison discussions |
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| **Hacker News** | Search `site:news.ycombinator.com "<product_name>"` | In-depth technical community discussions |
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| **Discord/Telegram** | Product's official community channels | Active user feedback (must annotate [limited source]) |
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## Principles
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- Conclusions must be traceable to L1/L2
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- L3/L4 serve only as supplementary and validation
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- L4 community discussions are used to discover "what users truly care about"
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- Record all information sources
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## Timeliness Filtering Rules (execute based on Step 0.5 sensitivity level)
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| Sensitivity Level | Source Filtering Rule | Suggested Search Parameters |
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|-------------------|----------------------|-----------------------------|
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| Critical | Only accept sources within 6 months as factual evidence | `time_range: "month"` or `start_date` set to last 3 months |
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| High | Prefer sources within 1 year; annotate if older than 1 year | `time_range: "year"` |
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| Medium | Sources within 2 years used normally; older ones need validity check | Default search |
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| Low | No time limit | Default search |
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## High-Sensitivity Domain Search Strategy
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```
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1. Round 1: Targeted official source search
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- Use include_domains to restrict to official domains
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- Example: include_domains: ["anthropic.com", "openai.com", "docs.xxx.com"]
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2. Round 2: Official download/release page direct verification (BLOCKING)
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- Directly visit official download pages; don't rely on search caches
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- Use tavily-extract or WebFetch to extract page content
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- Verify: platform support, current version number, release date
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3. Round 3: Product-specific protocol/feature search (BLOCKING)
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- Search protocol names the product supports (MCP, ACP, LSP, etc.)
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- Format: "<product_name> <protocol_name>" site:official_domain
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4. Round 4: Time-limited broad search
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- time_range: "month" or start_date set to recent
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- Exclude obviously outdated sources
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5. Round 5: Version verification
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- Cross-validate version numbers from search results
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- If inconsistency found, immediately consult official Changelog
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6. Round 6: Community voice mining (BLOCKING - mandatory for product comparison research)
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- Visit the product's GitHub Issues page, review popular/pinned issues
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- Search Issues for key feature terms (e.g., "MCP", "plugin", "integration")
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- Review discussion trends from the last 3-6 months
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- Identify the feature points and differentiating characteristics users care most about
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```
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## Community Voice Mining Detailed Steps
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```
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GitHub Issues Mining Steps:
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1. Visit github.com/<org>/<repo>/issues
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2. Sort by "Most commented" to view popular discussions
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3. Search keywords:
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- Feature-related: feature request, enhancement, MCP, plugin, API
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- Comparison-related: vs, compared to, alternative, migrate from
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4. Review issue labels: enhancement, feature, discussion
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5. Record frequently occurring feature demands and user pain points
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Value Translation:
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- Frequently discussed features -> likely differentiating highlights
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- User complaints/requests -> likely product weaknesses
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- Comparison discussions -> directly obtain user-perspective difference analysis
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```
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## Source Registry Entry Template
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For each source consulted, immediately append to `01_source_registry.md`:
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```markdown
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## Source #[number]
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- **Title**: [source title]
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- **Link**: [URL]
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- **Tier**: L1/L2/L3/L4
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- **Publication Date**: [YYYY-MM-DD]
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- **Timeliness Status**: Currently valid / Needs verification / Outdated (reference only)
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- **Version Info**: [If involving a specific version, must annotate]
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- **Target Audience**: [Explicitly annotate the group/geography/level this source targets]
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- **Research Boundary Match**: Full match / Partial overlap / Reference only
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- **Summary**: [1-2 sentence key content]
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- **Related Sub-question**: [which sub-question this corresponds to]
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```
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## Target Audience Verification (BLOCKING)
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Before including each source, verify that its target audience matches the research boundary:
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| Source Type | Target audience to verify | Verification method |
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|------------|---------------------------|---------------------|
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| **Policy/Regulation** | Who is it for? (K-12/university/all) | Check document title, scope clauses |
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| **Academic Research** | Who are the subjects? (vocational/undergraduate/graduate) | Check methodology/sample description sections |
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| **Statistical Data** | Which population is measured? | Check data source description |
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| **Case Reports** | What type of institution is involved? | Confirm institution type |
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Handling mismatched sources:
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- Target audience completely mismatched -> do not include
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- Partially overlapping -> include but annotate applicable scope
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- Usable as analogous reference -> include but explicitly annotate "reference only"
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# Usage Examples — Reference
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## Example 1: Initial Research (Mode A)
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```
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User: Research this problem and find the best solution
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```
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Execution flow:
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1. Context resolution: no explicit file -> project mode (INPUT_DIR=`_docs/00_problem/`, OUTPUT_DIR=`_docs/01_solution/`)
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2. Guardrails: verify INPUT_DIR exists with required files
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3. Mode detection: no `solution_draft*.md` -> Mode A
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4. Phase 1: Assess acceptance criteria and restrictions, ask user about unclear parts
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5. BLOCKING: present AC assessment, wait for user confirmation
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6. Phase 2: Full 8-step research — competitors, components, state-of-the-art solutions
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7. Output: `OUTPUT_DIR/solution_draft01.md`
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8. (Optional) Phase 3: Tech stack consolidation -> `tech_stack.md`
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9. (Optional) Phase 4: Security deep dive -> `security_analysis.md`
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## Example 2: Solution Assessment (Mode B)
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```
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User: Assess the current solution draft
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```
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Execution flow:
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1. Context resolution: no explicit file -> project mode
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2. Guardrails: verify INPUT_DIR exists
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3. Mode detection: `solution_draft03.md` found in OUTPUT_DIR -> Mode B, read it as input
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4. Full 8-step research — weak points, security, performance, solutions
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5. Output: `OUTPUT_DIR/solution_draft04.md` with findings table + revised draft
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## Example 3: Standalone Research
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```
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User: /research @my_problem.md
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```
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Execution flow:
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1. Context resolution: explicit file -> standalone mode (INPUT_FILE=`my_problem.md`, OUTPUT_DIR=`_standalone/my_problem/01_solution/`)
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2. Guardrails: verify INPUT_FILE exists and is non-empty, warn about missing restrictions/AC
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3. Mode detection + full research flow as in Example 1, scoped to standalone paths
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4. Output: `_standalone/my_problem/01_solution/solution_draft01.md`
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5. Move `my_problem.md` into `_standalone/my_problem/`
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## Example 4: Force Initial Research (Override)
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```
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User: Research from scratch, ignore existing drafts
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```
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Execution flow:
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1. Context resolution: no explicit file -> project mode
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2. Mode detection: drafts exist, but user explicitly requested initial research -> Mode A
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3. Phase 1 + Phase 2 as in Example 1
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4. Output: `OUTPUT_DIR/solution_draft##.md` (incremented from highest existing)
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Reference in New Issue
Block a user