indic_sentiment

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions cost ('$0.003 USDC') and service ('indic'), which adds useful context, but lacks critical details like rate limits, authentication needs, output format, or whether it's read-only or mutative. This is inadequate for a tool with potential external dependencies.

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 is concise with three short phrases, front-loading the core functionality. However, the cost and service details, while useful, could be integrated more smoothly, and it lacks structural elements like examples or bullet points that might enhance clarity without adding bulk.

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 tool's complexity (sentiment and emotion detection), no annotations, 0% schema coverage, and no output schema, the description is incomplete. It misses key details: parameter semantics, output structure, error handling, and behavioral constraints. The cost and service hints are helpful but insufficient for full contextual understanding.

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?

The schema description coverage is 0%, meaning parameters 'text' and 'language' are undocumented in the schema. The description fails to compensate by explaining what these parameters mean (e.g., 'text' as input for analysis, 'language' as code like 'hi' for Hindi), their formats, or valid values. This leaves parameters semantically unclear.

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 clearly states the tool performs 'sentiment analysis with emotion detection' and specifies the domain ('Indian languages including Hinglish'), which distinguishes it from siblings like 'analyze_call' or 'verify_claim'. However, it doesn't explicitly mention what resource it acts upon (e.g., text input) or differentiate from potential similar tools not in the sibling list.

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 provides minimal guidance: it implies usage for Indian language text analysis but offers no explicit when-to-use rules, prerequisites, or alternatives. For example, it doesn't specify when to choose this over 'indic_ner' (a sibling) or other sentiment tools, nor does it mention cost considerations as usage factors.

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