chore: sync .cursor skills from suite

.cursor/skills/research/SKILL.md

@@ -33,6 +33,24 @@ Transform vague topics raised by users into high-quality, deliverable research r
 - **Component option breadth** — for every component area, build a broad option landscape before selecting. Search direct candidates, adjacent-domain alternatives, commercial/open-source variants, classical/simple baselines, current SOTA, and "do not use" failure cases. A component may not be narrowed to one candidate until alternatives have been searched and rejected with evidence.
 - **Component research depth** — for every serious component candidate, go beyond discovery pages. Read official docs, repository/license files, issue discussions, benchmarks, deployment guides, version/platform requirements, security notes, maintenance signals, and real-world failure reports. Extract evidence for inputs/outputs, lifecycle assumptions, runtime/storage/latency fit, integration boundaries, licensing, operational risks, and unsupported scenarios before assigning any selection status.
 - **Exact-fit component selection** — never select a component, tool, library, service, architecture pattern, or algorithm merely because it solves a similar class of problem. It must be proven compatible with the project's explicit operating context, constraints, required inputs/outputs, non-functional requirements, lifecycle assumptions, and acceptance criteria. If fit is unproven or mismatched, mark it `Rejected`, `Experimental only`, or escalate for user decision before it can shape the solution.
+- **Per-mode API capability verification** *(applies only to technical-component selection — see Research Output Class below)* — when a candidate library/SDK/framework/service exposes multiple modes or configurations, *the candidate is not a single thing*. Pin the exact mode the project will use (one explicit sentence: inputs, outputs, runtime), and verify *that mode* against the project's required inputs/outputs via official docs (mandatory `context7` lookup) plus a saved Minimum Viable Example. Capability claims at the category level ("supports X, Y, Z modes") must be cross-checked against the literal mode enumeration before being treated as project-applicable. Two modes of one library are two distinct candidates for the purposes of the Component Applicability Gate. Does not apply to non-technical research (concept comparison, market/policy investigation, knowledge organization, etc.).
+
+## Research Output Class (BLOCKING — set in Step 1)
+
+Before applying any of the technical-component gates (per-mode API capability verification, Component Applicability Gate, Restrictions × Candidate-Mode sub-matrix, MVE evidence, mandatory `context7` lookup), classify the research output into one of two classes. Record the decision in `00_question_decomposition.md` once, near the top, so every downstream step honors it.
+
+| Class | What the output recommends or selects | Examples | Technical-component gates apply? |
+|-------|---------------------------------------|----------|----------------------------------|
+| **Technical-component selection** | One or more libraries, SDKs, frameworks, services, protocols, data formats, infrastructure patterns, algorithms, or APIs that will be implemented or operated against | "Pick a vector database", "Compare auth-token strategies for our API", "Should we use Kafka or RabbitMQ?", architecture / tech-stack / migration drafts (Mode A, Mode B) | **Yes — all gates active** |
+| **Non-technical investigation** | Concept comparisons, knowledge organization, root-cause investigation of an event, market/policy/regulatory/social analysis, literature review, decision support without committing to specific tooling | "Why did adoption stall in Q3?", "Compare phenomenology vs constructivism", "Map regulatory landscape for X", "What do practitioners say about onboarding under remote-first orgs?" | **No — skip API/MVE/sub-matrix gates; the rest of the 8-step engine still applies** |
+
+How to decide:
+1. Inspect the question and the input files (`problem.md`, `restrictions.md`, `acceptance_criteria.md`, or the standalone input file).
+2. If the deliverable will name specific software/services/protocols that someone will then build with or operate, it is **Technical-component selection**.
+3. If the deliverable is a report, comparison, or recommendation that does not commit to specific tooling, it is **Non-technical investigation**.
+4. **Mixed runs are valid.** Some research questions have a non-technical core but include one technical sub-question (or vice versa). In that case classify per component area within the run, not the run as a whole, and note in `00_question_decomposition.md` which component areas trigger the technical-component gates.
+
+When the run is purely **Non-technical investigation**, the rest of the research engine — question decomposition, perspective rotation, exhaustive web search, fact extraction, comparison framework, reasoning chain, validation, deliverable formatting — still applies in full. The sections that get skipped are explicitly the technical gates listed in the table above.
 
 ## Context Resolution