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- New vapora-capabilities crate: CapabilitySpec, Capability trait, CapabilityRegistry
(parking_lot RwLock), CapabilityLoader (TOML overrides), 3 built-ins
(code-reviewer, doc-generator, pr-monitor), 22 tests
- Move AgentDefinition to vapora-shared to break capabilities↔agents circular dep
- Wire system_prompt into AgentExecutor via LLMRouter.complete_with_budget
- AgentCoordinator: in-process task dispatch via DashMap<String, Sender<TaskAssignment>>
- server.rs: bootstrap CapabilityRegistry + LLMRouter from env, spawn executors per capability
- Landing page: 620 tests, 21 crates, Capability Packages feature box
- docs: capability-packages feature guide, ADR-0037, CHANGELOG, SUMMARY
EOF
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Markdown
# Capability Packages Guide
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## What Is a Capability Package
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A capability package bundles everything an agent needs to handle a specific domain into a single reusable unit. Activating one produces an `AgentDefinition` that the coordinator registers and routes tasks to.
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Each package carries:
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- `system_prompt` — domain-optimized instructions injected as the LLM system message before every task execution
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- `preferred_model` / `preferred_provider` — e.g. `claude-opus-4-6` for deep code reasoning, `claude-sonnet-4-6` for cost-efficient writing tasks
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- `task_types` — strings matched by the coordinator's `extract_task_type` heuristic against task titles and descriptions to select this agent
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- `mcp_tools` — list of MCP tool IDs (`file_read`, `git_diff`, etc.) activated for this agent via `vapora-mcp-server`
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- `temperature` / `max_tokens` / `priority` / `parallelizable` — execution parameters controlling output quality, cost, scheduling order, and concurrency
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## Built-in Capabilities
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| ID | Role | Model | Temp | Max Tokens | Use Case |
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|----|------|-------|------|------------|----------|
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| `code-reviewer` | `code_reviewer` | `claude-opus-4-6` | 0.1 | 8192 | Security and correctness review; JSON output with severity levels and `merge_ready` flag |
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| `doc-generator` | `documenter` | `claude-sonnet-4-6` | 0.3 | 16384 | Source-to-documentation generation with rustdoc/JSDoc/docstring output |
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| `pr-monitor` | `monitor` | `claude-sonnet-4-6` | 0.1 | 4096 | PR health check; `READY` / `NEEDS_REVIEW` / `BLOCKED` status output |
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The `code-reviewer` uses Opus 4.6 because review tasks benefit from deep reasoning over complex code patterns. Temperature 0.1 ensures reproducible findings across repeated runs on the same diff. `pr-monitor` is `parallelizable = false` — concurrent runs on the same PR would produce conflicting status reports.
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## Activating Built-ins at Runtime
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The agent server calls `CapabilityRegistry::with_built_ins()` at startup automatically. All three built-ins are registered and their executors spawned before the HTTP listener opens — no action required when running the standard agent server (`crates/vapora-agents`).
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For programmatic use:
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```rust
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use vapora_capabilities::CapabilityRegistry;
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let registry = CapabilityRegistry::with_built_ins();
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// "code-reviewer", "doc-generator", "pr-monitor" are now registered
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let def = registry.activate("code-reviewer")?;
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// def.role == "code_reviewer"
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// def.system_prompt == Some("<full review prompt>")
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// def.llm_model == "claude-opus-4-6"
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// def.llm_provider == "claude"
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```
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`activate` returns an `AgentDefinition` from `vapora-shared`. The system prompt is embedded in the definition and available at `def.system_prompt` — the executor injects it before every task without any further lookup.
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## Overriding a Built-in
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### Via TOML Config File
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Override fields are applied on top of the existing built-in spec. Only fields present in TOML are changed; everything else keeps its default. An unknown override `id` is skipped with a warning, not an error.
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```toml
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# config/capabilities.toml
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# Switch code-reviewer to Sonnet for cost savings
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[[override]]
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id = "code-reviewer"
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preferred_model = "claude-sonnet-4-6"
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max_tokens = 16384
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# Replace the doc-generator system prompt for your tech stack
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[[override]]
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id = "doc-generator"
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system_prompt = """
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You are a technical documentation specialist for Rust async systems.
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Follow rustdoc conventions. All examples must be runnable.
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"""
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```
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Load and apply at startup (or on config reload):
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```rust
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use vapora_capabilities::{CapabilityRegistry, CapabilityLoader};
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let registry = CapabilityRegistry::with_built_ins();
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CapabilityLoader::load_and_apply("config/capabilities.toml", ®istry)?;
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```
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`load_and_apply` reads the file, parses TOML, and applies overrides + custom entries in one call. The call is idempotent — re-applying the same file replaces existing specs rather than erroring.
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### Via the Registry API Directly
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```rust
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use vapora_capabilities::{CapabilityRegistry, CapabilitySpec, CustomCapability};
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let registry = CapabilityRegistry::with_built_ins();
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// Fetch the current spec, mutate it, push it back
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let mut spec = registry.get("code-reviewer").unwrap().spec();
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spec = spec.with_model("claude-sonnet-4-6").with_max_tokens(16384);
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registry.override_spec("code-reviewer", spec)?;
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// Returns CapabilityError::NotFound if the id is not registered
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// Returns CapabilityError::InvalidSpec if the spec id does not match the target id
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```
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## Adding a Custom Capability
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Custom entries in TOML are full `CapabilitySpec` definitions — all fields are required. They are registered with `register_or_replace`, so re-applying the config is safe.
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```toml
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[[custom]]
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id = "db-optimizer"
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display_name = "Database Optimizer"
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description = "Analyzes and optimizes SurrealQL queries and schema"
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agent_role = "db_optimizer"
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task_types = ["db_optimization", "query_review", "schema_review"]
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system_prompt = """
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You are a SurrealDB performance expert.
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Analyze queries and schema definitions for: index usage, full-table scans,
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unnecessary JOINs, missing composite indexes.
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Output JSON: { "issues": [...], "optimized_query": "...", "index_suggestions": [...] }
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"""
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mcp_tools = ["file_read", "code_search"]
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preferred_provider = "claude"
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preferred_model = "claude-sonnet-4-6"
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max_tokens = 4096
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temperature = 0.1
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priority = 75
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parallelizable = true
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```
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The `task_types` list must overlap with words present in task titles or descriptions. The coordinator's heuristic tokenizes the task text and checks for matches against registered task-type strings. If no match is found, the task falls back to default role assignment. Use lowercase snake\_case strings that reflect verbs and nouns users will write in task titles (`"query_review"`, `"db_optimization"`).
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## Environment Variables
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The agent server reads provider credentials from the environment at startup to configure the LLM router.
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| Variable | Effect |
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|----------|--------|
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| `LLM_ROUTER_CONFIG` | Path to a `llm-router.toml` file; takes precedence over all individual API key variables |
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| `ANTHROPIC_API_KEY` | Enables the `claude` provider; default model `claude-sonnet-4-6` |
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| `OPENAI_API_KEY` | Enables the `openai` provider; default model `gpt-4o` |
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| `OLLAMA_URL` | Enables the `ollama` provider (e.g. `http://localhost:11434`) |
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| `OLLAMA_MODEL` | Model used with Ollama (default: `llama3.2`) |
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| `BUDGET_CONFIG_PATH` | Path to budget config file (default: `config/agent-budgets.toml`) |
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If none of `LLM_ROUTER_CONFIG`, `ANTHROPIC_API_KEY`, `OPENAI_API_KEY`, or `OLLAMA_URL` are set, executors run in stub mode — tasks are accepted and return placeholder responses. This is intentional for integration tests and offline development.
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## Checking What Is Registered
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```rust
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let ids = registry.list_ids();
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// sorted alphabetically: ["code-reviewer", "doc-generator", "pr-monitor"]
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let count = registry.len(); // 3
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// Check and activate a specific capability
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if registry.contains("db-optimizer") {
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let def = registry.activate("db-optimizer")?;
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println!("role: {}, model: {}", def.role, def.llm_model);
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}
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// Iterate all registered capabilities (order is HashMap-based, not sorted)
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for cap in registry.list_all() {
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let spec = cap.spec();
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println!("{}: {} ({})", spec.id, spec.display_name, spec.preferred_model);
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}
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```
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## Capability Spec Field Reference
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| Field | Type | Description |
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|-------|------|-------------|
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| `id` | `String` | Unique kebab-case identifier (e.g., `"code-reviewer"`) |
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| `display_name` | `String` | Human-readable name shown in UIs and logs |
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| `description` | `String` | Brief purpose description embedded in the agent's log entries |
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| `agent_role` | `String` | Role name used by the coordinator for task routing (e.g., `"code_reviewer"`) |
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| `task_types` | `Vec<String>` | Keywords matched against task text by the coordinator heuristic |
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| `system_prompt` | `String` | Full system message injected before every task execution |
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| `mcp_tools` | `Vec<String>` | MCP tool IDs available to this agent via `vapora-mcp-server` |
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| `preferred_provider` | `String` | LLM provider name (`"claude"`, `"openai"`, `"ollama"`) |
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| `preferred_model` | `String` | Model ID within the provider (e.g., `"claude-opus-4-6"`) |
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| `max_tokens` | `u32` | Maximum output tokens per task execution |
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| `temperature` | `f32` | Sampling temperature 0.0–1.0; lower = more deterministic |
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| `priority` | `u32` | Assignment priority 0–100; higher = preferred when multiple agents match |
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| `parallelizable` | `bool` | Whether multiple instances may run concurrently for the same task type |
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## Writing Your Own Built-in
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Built-ins are unit structs in `crates/vapora-capabilities/src/built_in/`. Follow this pattern:
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```rust
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// crates/vapora-capabilities/src/built_in/sql_optimizer.rs
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use crate::capability::{Capability, CapabilitySpec};
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const SYSTEM_PROMPT: &str = r#"You are a SurrealDB query optimization expert.
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Analyze the provided query or schema definition.
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Output JSON: { "issues": [...], "optimized": "...", "indexes": [...] }"#;
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#[derive(Debug)]
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pub struct SqlOptimizer;
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impl Capability for SqlOptimizer {
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fn spec(&self) -> CapabilitySpec {
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CapabilitySpec {
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id: "sql-optimizer".to_string(),
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display_name: "SQL Optimizer".to_string(),
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description: "Optimizes SurrealQL queries and schema definitions".to_string(),
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agent_role: "sql_optimizer".to_string(),
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task_types: vec![
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"sql_optimization".to_string(),
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"query_review".to_string(),
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"schema_review".to_string(),
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],
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system_prompt: SYSTEM_PROMPT.to_string(),
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mcp_tools: vec!["file_read".to_string(), "code_search".to_string()],
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preferred_provider: "claude".to_string(),
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preferred_model: "claude-sonnet-4-6".to_string(),
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max_tokens: 4096,
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temperature: 0.1,
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priority: 75,
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parallelizable: true,
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}
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}
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}
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```
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Then wire it into the module and registry:
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```rust
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// crates/vapora-capabilities/src/built_in/mod.rs
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mod sql_optimizer;
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pub use sql_optimizer::SqlOptimizer;
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```
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```rust
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// crates/vapora-capabilities/src/registry.rs — inside with_built_ins()
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registry.register(SqlOptimizer).expect("sql-optimizer id collision");
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```
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The `expect` on `register` is intentional — built-in IDs are unique by construction, and a collision at startup indicates a programming error that must be caught during development, not at runtime.
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