chore: sync .cursor skills from suite

.cursor/skills/research/steps/03_engine-investigation.md

@@ -40,6 +40,7 @@ Key principle: Critical-sensitivity topics (AI/LLMs, blockchain) require sources
 - "What existing/competitor solutions address this problem?"
 - "What are the component parts of this problem?"
 - "For each component, what are the state-of-the-art solutions?"
+- "For each component, what are the practical alternatives across simple baseline, established production option, open-source option, commercial option, current SOTA, adjacent-domain option, and no-build/defer option?"
 - "What are the security considerations per component?"
 - "What are the cost implications of each approach?"
 
@@ -48,6 +49,7 @@ Key principle: Critical-sensitivity topics (AI/LLMs, blockchain) require sources
 - "What are the security vulnerabilities in the proposed architecture?"
 - "Where are the performance bottlenecks?"
 - "What solutions exist for each identified issue?"
+- "For each component already selected in the draft, what alternatives should be considered before keeping, replacing, or rejecting it?"
 
 **General sub-question patterns** (use when applicable):
 - **Sub-question A**: "What is X and how does it work?" (Definition & mechanism)
@@ -84,6 +86,27 @@ For **each sub-question**, generate **at least 3-5 search query variants** befor
 
 Record all planned queries in `00_question_decomposition.md` alongside each sub-question.
 
+#### Component Option Breadth (MANDATORY)
+
+Before Step 2, identify the component areas implied by the problem and create a search plan for options in each area. A component area is any replaceable tool, library, model, service, algorithm, data format, protocol, infrastructure pattern, or validation approach that could materially affect the solution.
+
+For every component area, generate search queries for these option families unless clearly not applicable:
+- **Simple baseline**: low-complexity classical or manual approach that can serve as a fallback or regression baseline.
+- **Established production option**: mature library/service/pattern with field usage.
+- **Open-source candidate**: permissive-license option with inspectable implementation and community history.
+- **Commercial/vendor option**: paid or vendor-supported option, including SDK/platform constraints.
+- **Current SOTA / research option**: recent model, paper, or benchmark leader that may be promising but immature.
+- **Adjacent-domain option**: solution from a neighboring domain with similar constraints.
+- **No-build / defer option**: whether the component can be avoided, simplified, or moved out of scope.
+- **Known bad option**: candidate or family that appears attractive but has documented failure modes or disqualifiers.
+
+For each component area, record:
+- Candidate names and option families to search.
+- At least 5 query variants covering alternatives, comparisons, limitations, licensing, runtime/scale, and exact project constraints.
+- The minimum evidence needed to mark a candidate `Selected`, `Rejected`, `Experimental only`, or `Needs user decision`.
+
+Add this as a "Component Option Search Plan" section in `00_question_decomposition.md`.
+
 **Research Subject Boundary Definition (BLOCKING - must be explicit)**:
 
 When decomposing questions, you must explicitly define the **boundaries of the research subject**:
@@ -94,6 +117,9 @@ When decomposing questions, you must explicitly define the **boundaries of the r
 | **Geography** | Which region is being studied? | Chinese universities vs US universities vs global |
 | **Timeframe** | Which period is being studied? | Post-2020 vs full historical picture |
 | **Level** | Which level is being studied? | Undergraduate vs graduate vs vocational |
+| **Operating context** | What exact environment, lifecycle phase, and runtime conditions must the solution support? | In-flight embedded runtime vs offline post-processing; production web traffic vs admin batch job |
+| **Required interfaces** | What inputs, outputs, protocols, data shapes, and ownership boundaries are fixed? | One camera vs stereo rig; REST API vs message queue; local file boundary vs service API |
+| **Non-functional envelope** | What latency, throughput, storage, memory, availability, safety, security, cost, and maintainability targets are binding? | <400 ms p95, 8 GB RAM, 99.9% availability, reversible migrations |
 
 **Common mistake**: User asks about "university classroom issues" but sources include policies targeting "K-12 students" — mismatched target populations will invalidate the entire research.
 
@@ -116,9 +142,11 @@ Record the audit result in `00_question_decomposition.md` as a "Completeness Aud
    - Summary of relevant problem context from INPUT_DIR
    - Classified question type and rationale
    - **Research subject boundary definition** (population, geography, timeframe, level)
+   - **Project Constraint Matrix summary** (operating context, required interfaces, non-functional envelope, lifecycle assumptions, and hard disqualifiers extracted from input files)
    - List of decomposed sub-questions
    - **Chosen perspectives** (at least 3 from the Perspective Rotation table) with rationale
    - **Search query variants** for each sub-question (at least 3-5 per sub-question)
+   - **Component Option Search Plan** (component areas, option families, candidate names, query variants, required evidence)
    - **Completeness audit** (taxonomy cross-reference + domain discovery results)
 4. Write TodoWrite to track progress
 
@@ -145,12 +173,30 @@ Do not stop at the first few results. The goal is to build a comprehensive evide
 - Consult at least **2 different source tiers** per sub-question (e.g., L1 official docs + L4 community discussion)
 - If initial searches yield fewer than 3 relevant sources for a sub-question, **broaden the search** with alternative terms, related domains, or analogous problems
 
+**Minimum search effort per component area**:
+- Search every option family from the "Component Option Search Plan" before choosing a lead candidate.
+- For each lead, fallback, or rejected candidate, search at least one official/source-of-truth page and at least one independent validation source when available.
+- Search `"[component] alternatives"`, `"[candidate] vs [alternative]"`, `"[candidate] limitations"`, `"[candidate] license"`, `"[candidate] production"`, and `"[candidate] [binding project constraint]"`.
+- If fewer than 3 realistic candidates are found for a component area, explicitly document why the landscape is narrow and search adjacent domains before accepting that result.
+- Include at least one simple baseline and one "do not use" or disqualified candidate per component area when possible; these prevent false confidence in the selected option.
+
+**Candidate implementation-limit searches (MANDATORY)**:
+For every component/tool/library/service/pattern/algorithm that may be selected or recommended, search for its intrinsic implementation constraints. Do not rely on product category labels, marketing summaries, or examples from a different operating context. Include query variants for:
+- Official supported inputs/outputs, protocols, data formats, and deployment modes
+- Required hardware/runtime/platform/version constraints
+- Timing, throughput, memory, storage, synchronization, and scaling assumptions
+- Lifecycle assumptions: offline vs online, batch vs real time, development vs production, single tenant vs multi tenant, local vs networked
+- Known unsupported scenarios, limitations, issue reports, production failures, and workarounds
+- Licensing, security, maintenance, and community-health constraints
+- Exact phrases from the project's restrictions and acceptance criteria combined with the candidate name
+
 **Search broadening strategies** (use when results are thin):
 - Try adjacent fields: if researching "drone indoor navigation", also search "robot indoor navigation", "warehouse AGV navigation"
 - Try different communities: academic papers, industry whitepapers, military/defense publications, hobbyist forums
 - Try different geographies: search in English + search for European/Asian approaches if relevant
 - Try historical evolution: "history of X", "evolution of X approaches", "X state of the art 2024 2025"
 - Try failure analysis: "X project failure", "X post-mortem", "X recall", "X incident report"
+- Try disqualifier probes: "X unsupported", "X limitations", "X requirements", "X with [project constraint]", "X without [required input]", "X real-time [target]", "X production failure"
 
 **Search saturation rule**: Continue searching until new queries stop producing substantially new information. If the last 3 searches only repeat previously found facts, the sub-question is saturated.
 
@@ -194,6 +240,7 @@ For each extracted fact, **immediately** append to `02_fact_cards.md`:
 - **Target Audience**: [which group this fact applies to, inherited from source or further refined]
 - **Confidence**: ✅/⚠️/❓
 - **Related Dimension**: [corresponding comparison dimension]
+- **Fit Impact**: [supports selection / disqualifies / makes experimental / needs user decision]
 ```
 
 **Target audience in fact statements**: