Method handleExplore

src/mcp/tools.ts:2619–3900

* Handle codegraph_explore — deep exploration in a single call * * Strategy: find relevant symbols via graph traversal, group by file, * then read contiguous file sections covering all symbols per file. * This replaces multiple codegraph_node + Read calls. * * Output size is adapti

(args: Record<string, unknown>)

   * tax on small projects while earning its keep on large ones.
   */
  private async handleExplore(args: Record<string, unknown>): Promise<ToolResult> {
    const rawQuery = this.validateString(args.query, 'query');
    if (typeof rawQuery !== 'string') return rawQuery;
    // One normalization point so the flow-builder, relevance search, and
    // ranking all see the same canonical spelling (Erlang `mod:fn/arity`).
    const query = normalizeQuerySpelling(rawQuery);

    const cg = this.getCodeGraph(args.projectPath as string | undefined);
    const projectRoot = cg.getProjectRoot();

    // Resolve adaptive output budget from project size. Falls back to the
    // largest-tier defaults if stats aren't available, which preserves
    // pre-#185 behavior for callers that hit the rare stats failure.
    let budget: ExploreOutputBudget;
    try {
      budget = getExploreOutputBudget(cg.getStats().fileCount);
    } catch {
      budget = getExploreOutputBudget(Infinity);
    }
    const maxFiles = clamp((args.maxFiles as number) || budget.defaultMaxFiles, 1, 20);

    // Step 1: Find relevant context with generous parameters.
    // Use a large maxNodes budget — explore has its own 35k char output limit
    // that prevents context bloat, so more nodes just means better coverage
    // across entry points (especially for large files like Svelte components).
    const subgraph = await cg.findRelevantContext(query, {
      searchLimit: 8,
      traversalDepth: 3,
      maxNodes: 200,
      minScore: 0.2,
    });

    if (subgraph.nodes.size === 0) {
      return this.textResult(`No relevant code found for "${query}"`);
    }

    // Graph-aware glue: findRelevantContext builds the subgraph from name/text
    // search, so a method that BRIDGES named symbols — e.g. App.tsx's
    // triggerRender, which calls the named triggerUpdate — is never a search hit
    // and gets missed, forcing the agent to Read the file to trace it. Pull in
    // the callers/callees of the entry (root) nodes, but ONLY those that live in
    // files the subgraph already surfaces (where the agent reads to fill gaps),
    // so we add wiring without dragging in unrelated files. These get an
    // importance boost below so they survive the per-file cluster budget.
    const glueNodeIds = new Set<string>();
    const subgraphFiles = new Set<string>();
    for (const n of subgraph.nodes.values()) subgraphFiles.add(n.filePath);
    const GLUE_NODE_CAP = 60;
    for (const rootId of subgraph.roots) {
      if (glueNodeIds.size >= GLUE_NODE_CAP) break;
      let neighbors: Node[] = [];
      try {
        neighbors = [
          ...cg.getCallers(rootId).map(c => c.node),
          ...cg.getCallees(rootId).map(c => c.node),
        ];
      } catch {
        continue;