impact-analysis

Impact Analysis

Analyze the impact of changing a symbol by finding all references and assessing risk. Use this BEFORE modifying widely-used symbols.

Process

Step 1: Resolve the change target

If the user gives you a symbol name, resolve the definition first so you know which file or symbol they mean:

fast_search(query="<symbol_name>", workspace="<workspace_id>")
deep_dive(symbol="<symbol_name>", context_file="<partial_file_path>", depth="overview", workspace="<workspace_id>")

Use context_file when the name is ambiguous. If the target is described conceptually rather than named exactly, try fast_search(query="<concept>", backend="semantic", workspace="<workspace_id>") or backend="hybrid" to find candidate symbols. Semantic/hybrid fast_search results are symbol-only; use explicit lexical for file paths and pure lexical comparison. Default fast_search may show labeled semantic fallback candidates only after an identifier-like unscoped lexical zero-hit. blast_radius(symbol_ids=[...], workspace="<workspace_id>") is the tightest seed mode, but only use it when another Julie result already gave you concrete symbol IDs. If all you have is a definition file, use file_paths=[...].

Step 2: One-shot impact via blast_radius

blast_radius(file_paths=["<definition_file>"], max_depth=2, include_tests=true, workspace="<workspace_id>")

blast_radius is the primary entry point for impact analysis. One call returns ranked impacted symbols with why-reasons and likely tests. It walks the reference graph deterministically, so you don't have to chain get_context → fast_refs → deep_dive to build the same picture.

You can seed it three ways:

• file_paths=["src/foo.rs"] — default when you know the changed file but not a symbol ID
• symbol_ids=["<id>"] — tighter impact when another Julie result already gave you concrete symbol IDs

If the impact list is large, the output ends with Output truncated at <N> results; narrow the query or pass a smaller limit. See Step 4.