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Guides when to use MCP tools over basic tools (Read/Grep/Glob/Bash) for semantic search, AI analysis, research, and image generation. Enforces the search_tools → get_tool_schema → execute_code workflow.
npx claudepluginhub espalier-redoubt/claudikins-tool-executorHow this skill is triggered — by the user, by Claude, or both
Slash command
/claudikins-tool-executor:using-tool-executorThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
<IMPORTANT>
Invokes MCP tools via tool-executor for semantic code search, refactoring, AI research, image generation, and library docs when basic tools fall short.
Discovers Claude Code tool environment including native tools and MCP servers via scans, amplifies prompts with capabilities, and suggests non-binding tool compositions for 'what tools to use' or 'best approach' queries.
Triggers research for existing libraries, tools, and patterns before coding new features. Searches npm, PyPI, MCP/skills, GitHub; evaluates matches and decides adopt/extend/build.
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Use the right tool for the job:
| Task | Use This | NOT This |
|---|---|---|
| Read a file | Read tool | MCP |
| Search for literal string | Grep tool | MCP |
| Find files by pattern | Glob tool | MCP |
| Run shell commands | Bash tool | MCP |
| Semantic code search | MCP (Serena) | Grep |
| Refactor/rename symbols | MCP (Serena) | Edit |
| Deep research | MCP (Gemini) | WebSearch |
| AI-powered analysis | MCP (Gemini) | - |
| Generate images/video | MCP (Gemini) | - |
| Library documentation | MCP (Context7) | WebFetch |
| Multi-step reasoning | MCP (Sequential) | - |
Basic tools are great for basic tasks. MCP is for capabilities that don't exist in basic tools.
**When you DO use tool-executor, you MUST follow the workflow.**You don't know the exact tool names or schemas. You must discover them.
This is not negotiable. This is not optional. You cannot guess your way through MCP.
EVERY tool-executor interaction follows this sequence:
1. search_tools(query) → Find relevant tools
2. get_tool_schema(name) → Get exact parameters
3. execute_code(code) → Run the tool
digraph tool_flow {
"Need MCP capability" [shape=doublecircle];
"Know exact tool name?" [shape=diamond];
"search_tools(query)" [shape=box];
"get_tool_schema(name)" [shape=box];
"execute_code with tool" [shape=box];
"Handle result" [shape=doublecircle];
"Need MCP capability" -> "Know exact tool name?";
"Know exact tool name?" -> "search_tools(query)" [label="NO (99% of cases)"];
"Know exact tool name?" -> "get_tool_schema(name)" [label="YES (rare)"];
"search_tools(query)" -> "get_tool_schema(name)";
"get_tool_schema(name)" -> "execute_code with tool";
"execute_code with tool" -> "Handle result";
}
| Category | Server | Capabilities |
|---|---|---|
| code-nav | Serena (28 tools) | Symbol search, refactoring, code analysis, persistent memory |
| knowledge | Context7, NotebookLM | Library docs lookup, notebook Q&A, research |
| ai-models | Gemini (37 tools) | Deep research, brainstorming, image gen, video gen, structured output |
| reasoning | Sequential-thinking | Multi-step reasoning with thought chains |
| ui | shadcn | Component search, examples, implementation |
| web | Apify | Web scraping, RAG browser, data extraction |
When deciding WHETHER to use MCP:
| Thought | Reality |
|---|---|
| "I'll use Serena to read this file" | Just use Read tool. Serena is for semantic search. |
| "I need MCP to search for 'TODO'" | Grep is fine for literal strings. |
| "Let me use Gemini to check the file" | Read it yourself. Gemini is for analysis/research. |
When you ARE using MCP:
| Thought | Reality |
|---|---|
| "I remember the tool name" | Tool names change. Search first. |
| "I know the schema" | Schemas evolve. Get fresh schema. |
| "Let me just try execute_code" | Without search/schema = guaranteed failure. |
| "I'll console.log the result" | Large outputs truncate. Use workspace. |
| "Let me Read that _savedTo path" | Workspace isn't filesystem. Use workspace.readJSON(). |
| "search_tools is overhead" | search_tools prevents 10x more overhead from failures. |
Large MCP responses are auto-saved to workspace. You receive:
{ _savedTo: "mcp-results/123.json", _preview: "..." }
DO NOT try to Read("mcp-results/123.json") - that path doesn't exist on the filesystem!
DO use execute_code to access it:
const data = await workspace.readJSON("mcp-results/123.json");
console.log(JSON.stringify(data, null, 2));
Best practice - save your own outputs too:
const result = await gemini["gemini-deep-research"]({ query: "..." });
// If result has _savedTo, it's already saved
if (result._savedTo) {
const full = await workspace.readJSON(result._savedTo);
// Process full data...
await workspace.writeJSON("my-analysis.json", processedData);
console.log("Saved to my-analysis.json"); // Minimal console output
}
Use basic tools for:
ReadGrepGlobBashEditUse MCP for (via search_tools first!):
find_symbol)rename_symbol)query-docs)gemini-deep-research)gemini-brainstorm)gemini-analyze-code)gemini-generate-image)search_components)call-actor)Before ANY tool-executor usage:
search_tools → get_tool_schema → execute_code
Every. Single. Time.
No exceptions. No shortcuts. No guessing.