Back to Skills

lsp-impact

blackwell-systems
Updated 6 days ago
53
2
53
View on GitHub
Othergeneral

About

This skill performs blast-radius analysis for code symbols or files, showing callers, type hierarchies, and reference counts to assess impact before changes. It's designed for refactoring, deletions, or signature modifications, helping developers understand dependencies. The tool works with the agent-lsp MCP server and accepts either a symbol name or file path for comprehensive exported-symbol impact analysis.

Quick Install

Claude Code

Recommended
Primary
npx skills add blackwell-systems/agent-lsp -a claude-code
Plugin CommandAlternative
/plugin add https://github.com/blackwell-systems/agent-lsp
Git CloneAlternative
git clone https://github.com/blackwell-systems/agent-lsp.git ~/.claude/skills/lsp-impact

Copy and paste this command in Claude Code to install this skill

Documentation

Requires the agent-lsp MCP server.

lsp-impact

Blast-radius analysis for any symbol or file. Discovers all direct references, callers (via call hierarchy), and type relationships before you touch anything. Read-only — does not modify any files.

Run this skill before lsp-edit-export: impact tells you what exists and how widespread the change is; lsp-edit-export tells you how to execute the change safely.

Invocation:

  • File path (e.g. "internal/lsp/client.go") → use the File-level entry (Step 0) to surface all exported-symbol impact at once.
  • Symbol name in dot notation (e.g. "codec.Encode", "Buffer.Reset") → skip Step 0; start at Prerequisites, then Step 1.

Step 0 — File-level entry (when user provides a file path)

Use this shortcut when the user is changing or auditing an entire file rather than a single symbol. blast_radius enumerates all exported symbols in the file, resolves their references, and returns test callers (with enclosing test function names) and non-test callers in a single call.

mcp__lsp__blast_radius({
  "changed_files": ["/abs/path/to/file.go"],
  "include_transitive": false   // set true to surface second-order callers
})

Returns:

  • affected_symbols — each exported symbol with its reference count
  • test_callers — test files + enclosing test function names
  • non_test_callers — production call sites

Decision after Step 0:

ResultAction
0 non-test callersLow blast radius. Proceed with change.
Few callers, known filesMedium risk. Update each call site.
Many callers across packagesHigh risk. Consider staged rollout.
Want symbol-level detailContinue to Steps 1–5 for any specific symbol.

Skip Steps 1–5 if the file-level summary is sufficient.


Prerequisites (for symbol-level Steps 1–5)

If LSP is not yet initialized, call mcp__lsp__start_lsp with the workspace root first.

Check what the server supports before proceeding — find_callers and type_hierarchy are optional LSP features not implemented by all servers:

mcp__lsp__get_server_capabilities()

Note which tools appear in supported_tools. Steps 3 and 4 below depend on this result.


Step 1 — Locate the symbol

Use go_to_symbol with the symbol name provided by the user:

mcp__lsp__go_to_symbol({
  "symbol_path": "Package.SymbolName",
  "workspace_root": "/abs/path"   // optional, narrows scope
})
→ returns: file, line, column (1-indexed)

symbol_path uses dot notation. For a top-level function Encode in package codec, use "codec.Encode". For a method Reset on type Buffer, use "Buffer.Reset".

Record the returned file, line, and column — you will pass them to every subsequent step.


Step 2 — Enumerate all direct references (always available)

Call find_references with include_declaration: false to find every usage site across the workspace:

mcp__lsp__find_references({
  "file_path": "<file from Step 1>",
  "position_pattern": "func @@SymbolName(",   // adjust prefix for symbol kind
  "include_declaration": false
})

Collect all reference locations. Group results by file. Record the total count and list of files — these feed the Impact Report.

See references/patterns.md for position_pattern examples by language and symbol kind.


Step 3 — Call hierarchy (callers and callees)

Only if find_callers appears in supported_tools from Step 0.

mcp__lsp__find_callers({
  "file_path": "<file from Step 1>",
  "line": <line from Step 1>,
  "column": <column from Step 1>,
  "direction": "incoming"   // use "both" if callees are also needed
})

If find_callers is not in supported_tools, skip this step entirely. Note "call hierarchy not supported by this server" in the Impact Report.


Step 4 — Type hierarchy (supertypes and subtypes)

Only applicable when the symbol is a type, interface, or class (not a plain function or method). Only if type_hierarchy appears in supported_tools.

mcp__lsp__type_hierarchy({
  "file_path": "<file from Step 1>",
  "line": <line from Step 1>,
  "column": <column from Step 1>,
  "direction": "both"
})

If the symbol is a function or method: skip this step; note "not applicable (function)" in the report.

If type_hierarchy is not in supported_tools: skip this step; note "not supported by this server" in the report.


Step 5 — Report impact surface

Produce the Impact Report using the format defined in references/patterns.md.

Include:

  • Symbol name, kind, and definition location
  • Reference count and list of files containing references
  • Callers from find_callers incoming (or skip note)
  • Supertypes and subtypes from type_hierarchy (or skip note)
  • Blast radius: count of distinct files affected

Then apply the decision guide:

Blast radiusRecommendation
0 referencesLikely dead code. Confirm with lsp-dead-code before deleting.
1–5 filesLow risk. Proceed. Update all callers.
6–20 filesMedium risk. Plan changes carefully. Stage in waves.
> 20 filesHigh risk. Consider a deprecation path or feature flag.

Example

Goal: assess blast radius of exported function `ParseConfig` in pkg/config

Prerequisites — get_server_capabilities:
  → supported_tools: [go_to_symbol, find_references, find_callers, ...]
  → type_hierarchy: not in supported_tools

Step 1 — go_to_symbol: symbol_path="config.ParseConfig"
  → pkg/config/parser.go:42:6

Step 2 — find_references: position_pattern="func @@ParseConfig("
  → 7 references in 4 files
  → cmd/main.go, internal/app.go, internal/loader.go, pkg/config/parser_test.go

Step 3 — find_callers: direction="incoming"
  → callers: cmd.main (cmd/main.go:14), app.Start (internal/app.go:31), ...

Step 4 — type_hierarchy: skipped (function), also not supported by server

Step 5 — Impact Report:
  ## Impact Report: ParseConfig
  - Kind:         function
  - Definition:   pkg/config/parser.go:42:6
  - References:   7 across 4 files
  ...
  - Risk level:   low

Note on position_pattern

position_pattern with @@ is a agent-lsp extension. If your MCP client does not support it, fall back to explicit line and column parameters from the location returned by go_to_symbol in Step 1.

GitHub Repository

blackwell-systems/agent-lsp
Path: skills/lsp-impact
0
agentskillsai-agentsai-toolingclaudeclaude-codecode-intelligence

Related Skills

llamaguard

Other

LlamaGuard is Meta's 7-8B parameter model for moderating LLM inputs and outputs across six safety categories like violence and hate speech. It offers 94-95% accuracy and can be deployed using vLLM, Hugging Face, or Amazon SageMaker. Use this skill to easily integrate content filtering and safety guardrails into your AI applications.

View skill

cost-optimization

Other

This Claude Skill helps developers optimize cloud costs through resource rightsizing, tagging strategies, and spending analysis. It provides a framework for reducing cloud expenses and implementing cost governance across AWS, Azure, and GCP. Use it when you need to analyze infrastructure costs, right-size resources, or meet budget constraints.

View skill

quantizing-models-bitsandbytes

Other

This skill quantizes LLMs to 8-bit or 4-bit precision using bitsandbytes, achieving 50-75% memory reduction with minimal accuracy loss. It's ideal for running larger models on limited GPU memory or accelerating inference, supporting formats like INT8, NF4, and FP4. The skill integrates with HuggingFace Transformers and enables QLoRA training and 8-bit optimizers.

View skill

dispatching-parallel-agents

Other

This Claude Skill dispatches multiple agents to investigate and fix 3+ independent problems concurrently. It is designed for scenarios involving unrelated failures that can be resolved without shared state or dependencies. The core capability is parallel problem-solving, assigning one agent per independent problem domain to maximize efficiency.

View skill