netintel_text_chunk

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

With no annotations, the description carries the full burden and does well: it declares determinism (same input → same chunks), that no API key or LLM is involved, and that output includes chunk index and start/end offsets. It stops short of describing error behavior or the default values applied when unit/size/overlap are omitted.

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?

Front-loaded with the core action and use case, then supporting traits in a compact clause. Efficient overall, though the trailing ellipsis suggests the text is truncated and some detail may be lost.

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?

No output schema exists, and the description steps in by describing the return shape (each chunk with index and offsets). For a 4-param text utility with zero annotation coverage, the remaining gap is parameter defaults and edge-case behavior.

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 coverage is 0%, so the description must compensate. It does explain that chunks are unit-based (characters or words) and that chunk size and overlap are configurable, but it never clarifies that 'text' is the required input or what defaults apply to unit/chunk_size/overlap. Partial compensation for four undocumented params.

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?

States a specific verb and resource ('split text into overlapping chunks') with the intended use case (RAG ingestion) and the configurable dimensions (characters or words, size, overlap). An agent can distinguish this from netintel_text_summarize or netintel_text_stats without opening any schema.

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 phrase 'for RAG ingestion' gives clear implied usage context, but the description never states when to prefer this over sibling text tools (summarize, stats, embed) or any exclusions/preconditions. Usage is inferable rather than explicit.

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