Constellation

Tool Scores

• code_intelA
  4.6/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Annotations cover the safety profile (readOnly, idempotent, non-destructive). The description adds valuable behavioral context: it explains the graph-backed analysis capability, notes that queries are case-insensitive substring matches, warns about breaking change risks, and documents the available API methods (searchSymbols, impactAnalysis, etc.) that can be called within the code parameter.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  While lengthy, the description is well-structured with clear section headers (DECISION RULE, QUICK START, WHY THIS TOOL, USE IMMEDIATELY WHEN) that allow scanning. The content is front-loaded with the critical decision rule and quick start. Every section serves a distinct purpose for this complex meta-tool that executes arbitrary JavaScript code.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's complexity (arbitrary code execution against a code intelligence API) and the presence of an output schema, the description is remarkably complete. It documents all available API methods, provides usage patterns for the five most common questions, explains project capability detection, and outlines typical workflows. No significant gaps remain.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema coverage is 100%, establishing a baseline of 3. The description adds significant value by providing concrete usage examples for the 'code' parameter (e.g., 'return await api.searchSymbols({query: "AuthService"})'), explaining that 'cwd' locates constellation.json via git root, and emphasizing the cwd requirement. This compensates for the abstract nature of the 'code' parameter.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description explicitly distinguishes structure questions (definitions, callers, impact) from text search, using specific verbs like 'Graph-backed intelligence finds indirect relationships, transitive dependencies.' It clearly identifies the resource (code structure/symbols) and scope, differentiating from text-based alternatives.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines5/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  Provides explicit decision rules ('Structure questions → this tool. Text search → Grep'), lists specific scenarios for immediate use ('BEFORE using Edit,' 'BEFORE refactoring'), names alternatives explicitly (Grep, Glob, Read), and includes a 'WRONG TOOL SIGNAL' to prevent misuse. This is exemplary guidance.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.