Fix tidy and sync package-lock.json

Author: data-douser

docs/ql-mcp/prompts.md

@@ -8,19 +8,19 @@ The server provides **11 prompts** that guide AI assistants through common CodeQ
 
 ## Prompt Reference
 
-| Prompt                         | Description                                                                                                          |
-| ------------------------------ | -------------------------------------------------------------------------------------------------------------------- |
-| `document_codeql_query`        | Create or update documentation for a CodeQL query                                                                    |
-| `explain_codeql_query`         | Generate a detailed explanation of a CodeQL query for workshop learning content                                      |
-| `ql_lsp_iterative_development` | Iterative CodeQL query development using LSP tools for completion, navigation, and validation                        |
-| `ql_tdd_advanced`              | Advanced test-driven CodeQL development with AST visualization, control flow, and call graph analysis                |
-| `ql_tdd_basic`                 | Test-driven CodeQL query development checklist — write tests first, implement query, iterate until tests pass        |
+| Prompt                                    | Description                                                                                                          |
+| ----------------------------------------- | -------------------------------------------------------------------------------------------------------------------- |
+| `document_codeql_query`                   | Create or update documentation for a CodeQL query                                                                    |
+| `explain_codeql_query`                    | Generate a detailed explanation of a CodeQL query for workshop learning content                                      |
+| `ql_lsp_iterative_development`            | Iterative CodeQL query development using LSP tools for completion, navigation, and validation                        |
+| `ql_tdd_advanced`                         | Advanced test-driven CodeQL development with AST visualization, control flow, and call graph analysis                |
+| `ql_tdd_basic`                            | Test-driven CodeQL query development checklist — write tests first, implement query, iterate until tests pass        |
 | `run_query_and_summarize_false_positives` | Run a CodeQL query and summarize its false positives                                                                 |
-| `sarif_rank_false_positives`   | Analyze SARIF results to identify likely false positives in CodeQL query results                                     |
-| `sarif_rank_true_positives`    | Analyze SARIF results to identify likely true positives in CodeQL query results                                      |
-| `test_driven_development`      | Test-driven development workflow for CodeQL queries using MCP tools                                                  |
-| `tools_query_workflow`         | Guide for using built-in tools queries (PrintAST, PrintCFG, CallGraphFrom, CallGraphTo) to understand code structure |
-| `workshop_creation_workflow`   | Guide for creating CodeQL query development workshops from production-grade queries                                  |
+| `sarif_rank_false_positives`              | Analyze SARIF results to identify likely false positives in CodeQL query results                                     |
+| `sarif_rank_true_positives`               | Analyze SARIF results to identify likely true positives in CodeQL query results                                      |
+| `test_driven_development`                 | Test-driven development workflow for CodeQL queries using MCP tools                                                  |
+| `tools_query_workflow`                    | Guide for using built-in tools queries (PrintAST, PrintCFG, CallGraphFrom, CallGraphTo) to understand code structure |
+| `workshop_creation_workflow`              | Guide for creating CodeQL query development workshops from production-grade queries                                  |
 
 ## Prompt Categories
 

package-lock.json

@@ -12,12 +12,12 @@ Help a developer discover what kinds of false positives are produced by their cu
 
 1. Read the provided CodeQL query to understand what patterns it is designed to detect.
 2. Discover the results of this query on a real database, by:
-    - Running the tool `list_query_run_results` to find existing runs for this query
-    - If no existing runs are found, run the query on a relevant database using `codeql_query_run` tool
+   - Running the tool `list_query_run_results` to find existing runs for this query
+   - If no existing runs are found, run the query on a relevant database using `codeql_query_run` tool
 3. Analyze and group the results into what appear to be similar types of results. This may mean:
-    - Grouping results in the same file
-    - Grouping results that reference the same elements
-    - Grouping results with similar messages
+   - Grouping results in the same file
+   - Grouping results that reference the same elements
+   - Grouping results with similar messages
 4. For each group, explore the actual code for a sample of alerts in that group, using the `read_database_source` tool to triage the results and determine which groups appear to be false positives
 5. For each false positive case discovered in this exploration, group them into categories of similar root causes. For example, a query might not properly account for unreachable code, or there may be a commonly used library that violates the query's assumptions but is actually safe.
 6. Explain these results to the user in order of most common to least common, so they can understand where their query may need improvement to reduce false positives.
@@ -77,7 +77,6 @@ The tool `read_database_source` can be used to read the code of a particular fin
 - **Mark uncertainty**: Use lower confidence scores when code snippets are missing
 - **Avoid false confidence**: If you cannot determine FP status, mark confidence as low
 
-
 ## Output Format
 
 Return a JSON array of ranked results, ordered by FP likelihood (highest first):