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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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Oleksandr Bezdieniezhnykh
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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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