codebase_context_index

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

Discloses that it chunks and embeds artifact content into the vector database, implying modification of the index. However, no annotations exist; description could be more detailed about side effects (e.g., overwriting existing index) but is sufficient for typical use.

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

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

Extremely concise: two sentences. First sentence states core action, second provides usage guidance. No filler or redundancy.

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

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

Adequately describes the tool's purpose and when to use it. No output schema, but for an indexing action the return value is likely straightforward. Could mention whether it returns success status, but overall complete given the tool's simple nature.

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

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

Schema covers 100% of parameters (projectPath with clear description). Description adds minimal extra meaning beyond schema, referencing the config file but not enhancing parameter semantics significantly. Baseline 3 is appropriate.

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

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

Clearly states indexing/re-indexing of context artifacts from .socraticodecontextartifacts.json. Specifies the process of chunking and embedding into vector database for semantic search. Distinguishes from sibling codebase_context_search by noting auto-indexing.

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

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

Explicitly advises when to use (rarely needed) and provides alternative (codebase_context_search auto-indexes). This guides the agent to prefer the search tool unless manual indexing is required.

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