jambavan_context

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

With no annotations provided, the description fully discloses the behavioral traits: ranking, token-budgeting, returning only relevant symbol bodies. It conveys a non-destructive, read-only search operation without contradicting any annotations.

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?

The description consists of four concise sentences, each contributing essential information: purpose, result characteristics, usage suggestion, and value proposition. No superfluous text.

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?

Given the absence of an output schema, the description adequately explains the return format (ranked, token-budgeted context block). It covers the tool's core functionality and use case, though it lacks explicit error/edge-case handling.

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 description coverage is 100%, so the baseline is 3. The description adds meaningful context beyond the schema by explaining that 'query' accepts natural-language or identifier queries, and 'limit' involves token-budget truncation, which aids correct usage.

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?

The description uses specific verbs ('search', 'returns', 'inject') and clearly identifies the resource ('Jambavan index', 'code symbols and snippets'). It distinguishes from sibling tools by highlighting cost efficiency and targeted retrieval ('token-budgeted', 'cheaper than reading whole files').

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?

The description explicitly advises injecting the result into the prompt for precise, token-efficient codebase knowledge and compares favorably to reading whole files. It does not explicitly list alternatives or when not to use, but the context is clear enough for an agent to decide.

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