Windsurf + Aider targets, MCP server, and demo placement (#33)

Broadens both reach (more tools) and content types (an MCP server), continuing the multi-platform story. Windsurf + Aider: - build-exports.mjs gains two platforms: exports/windsurf/*.md (workspace rules, trigger: model_decision) and exports/aider/*.md (conventions for `aider --read`). Now 5 platforms (ChatGPT, Gemini, Cursor, Windsurf, Aider). - install.sh + bin/cli.mjs install both (windsurf -> .windsurf/rules, aider -> .aider/skills with a --read hint); generated README index is excluded from copies. - One-line windsurf-install.sh / aider-install.sh wrappers for parity. MCP server (new content type): - mcp/server.mjs — zero-dependency stdio MCP server exposing list_skills, search_skills, get_skill. Published as a second bin (pm-claude-skills-mcp). Logs to stderr; reads bundled skills/ at startup. mcp/README.md documents client config. Also: README hero "See it in action" demo placement (ready to swap in a GIF; recording guide in web/docs-assets/README.md), Works-With table + exports + install docs updated, CHANGELOG Unreleased. package.json files/bin updated. Claude-Session: https://claude.ai/code/session_016JWn5jRD5tcEFKrubjQ6Px Co-authored-by: Claude <noreply@anthropic.com>
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+---
+trigger: model_decision
+description: "Explains, optimises, writes, and documents SQL queries. Use when asked to explain a SQL query, optimise slow SQL, translate SQL to plain English for non-technical stakeholders, write a query from a natural language description, or produce query documentation. Produces plain-English explanations, annotated optimised queries, or a data dictionary covering output shape, assumptions, and known limitations. Works across PostgreSQL, MySQL, BigQuery, Snowflake, and standard SQL."
+---
+
+# SQL Query Explainer Skill
+
+This skill explains SQL queries in plain language, identifies optimisation opportunities, and helps communicate data logic to non-technical stakeholders. It also writes and documents new queries from natural language descriptions.
+
+## Modes
+
+Detect which mode the user needs based on their request:
+
+1. **Explain** — Translate existing SQL into plain English
+2. **Optimise** — Review SQL for performance issues and suggest improvements
+3. **Write** — Generate SQL from a natural language description
+4. **Document** — Produce a data dictionary or query documentation
+
+---
+
+## Mode 1: Explain
+
+When given a SQL query, produce:
+
+### Plain English Summary
+[1–3 sentences. What does this query do? What data does it return? Write as if explaining to a business analyst, not a developer.]
+
+### Step-by-Step Walkthrough
+
+Break the query into logical sections. For each section:
+- Quote the SQL clause
+- Explain what it does in plain English
+- Flag any complexity (e.g. window functions, subqueries, CTEs)
+
+### What the Result Looks Like
+
+[Describe the shape of the output: "Returns one row per user, with columns for X, Y, Z. Ordered by [field] descending."]
+
+### Potential Issues to Flag
+
+- [Gotchas, edge cases, or implicit assumptions in this query]
+- [e.g. "This will include NULLs in the user_id column if the LEFT JOIN finds no match"]
+
+---
+
+## Mode 2: Optimise
+
+When asked to optimise a query, produce:
+
+### Performance Assessment
+
+Rate overall: 🟢 Well-optimised / 🟡 Some improvements possible / 🔴 Significant issues
+
+### Issues Found
+
+For each issue:
+
+**Issue [N]: [Short name, e.g. "Missing index on join column"]**
+- **What it is:** [Plain explanation]
+- **Why it matters:** [Performance impact — e.g. "Full table scan on a 10M row table"]
+- **Fix:**
+```sql
+-- Before
+[original snippet]
+
+-- After
+[improved snippet]
+```
+- **Expected improvement:** [Estimate if possible]
+
+### Optimisation Checklist
+
+- [ ] SELECT * used? (Replace with specific columns)
+- [ ] Implicit type conversions on JOIN/WHERE columns?
+- [ ] Missing indexes on JOIN or WHERE columns?
+- [ ] N+1 patterns (queries inside loops)?
+- [ ] DISTINCT used where GROUP BY would be faster?
+- [ ] Window functions used where a subquery would be clearer/faster?
+- [ ] CTEs re-used or materialised unnecessarily?
+- [ ] Large IN() lists that could use a JOIN instead?
+
+---
+
+## Mode 3: Write
+
+When given a natural language description, generate the SQL query and then explain it using Mode 1.
+
+Ask the user to confirm:
+- **Database/dialect** (PostgreSQL / MySQL / BigQuery / Snowflake / SQLite / Standard SQL)
+- **Table and column names** (if known; otherwise use descriptive placeholder names like `users`, `orders`, `user_id`)
+- **Any filters, sorting, or aggregation requirements**
+
+Produce:
+1. The SQL query with inline comments
+2. Plain English explanation (Mode 1 format)
+
+---
+
+## Mode 4: Document
+
+When asked to create documentation for a query or table:
+
+### Query Documentation
+
+```
+Query: [Name]
+Purpose: [One sentence — what business question this answers]
+Author: [If provided]
+Last reviewed: [If provided]
+
+Inputs:
+  - Table: [table_name] — [what it contains]
+  - Filter: [any WHERE conditions and their business meaning]
+
+Output columns:
+  | Column | Type | Description |
+  |--------|------|-------------|
+  | [name] | [type] | [plain English description] |
+
+Assumptions:
+  - [Any implicit assumptions the query makes]
+
+Known limitations:
+  - [Edge cases not handled, data quality dependencies, etc.]
+```
+
+---
+
+## Quality Checks
+
+- [ ] Plain English explanation avoids SQL jargon
+- [ ] Optimisation suggestions include before/after SQL
+- [ ] Written queries include inline comments
+- [ ] Output shape is described (columns, row grain, ordering)
+- [ ] Dialect-specific syntax is flagged when non-standard
+
+## Example Trigger Phrases
+
+- "Explain this SQL query: [paste query]"
+- "Optimise this slow query: [paste query]"
+- "Write a SQL query that [natural language description]"
+- "Document this query for my non-technical stakeholders"
+- "Why is this query returning unexpected results?"