fetch_targeted_data

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

No annotations are provided, so the description carries the full behavioral burden. The verbs 'fetch' and 'extraction' strongly imply a read-only operation, and format-dependent behavior plus offset/limit semantics are given, but there is no explicit non-mutation guarantee, error behavior, or authentication context.

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 front-loaded with the core purpose and then structured as four tight, format-specific bullets. Every sentence earns its place and there is no redundant or filler 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 high parameter count (9), 0% schema coverage, and no annotations, the description does a strong job covering format support and parameter mapping; the output schema already handles return values. It is slightly incomplete on usage alternatives and behavioral caveats, but it is sufficient for an agent to call the tool correctly.

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 0% across 9 parameters, so the description must compensate. It maps `query` to SQL and JSON path expressions with concrete examples, `columns`/`row_offset`/`row_limit`/`filter_col`/`filter_value` to CSV/TSV filtering, and `start_line`/`end_line` to text extraction. Only `rel_path` and parameter defaults remain unexplained, so the compensation is substantial.

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 states a specific verb ('fetch') and resource ('targeted data against structured files'), then enumerates the exact file formats supported (SQLite, JSON/JSONL, CSV/TSV, text/code). It does not name any sibling tool to differentiate itself, but the multi-format querying capability is distinctive enough for an agent to recognize it.

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 bullets imply when to use which parameter by mapping them to file types, which is useful implied guidance. However, there is no explicit when-to-use or when-not-to-use statement, and no alternative sibling (e.g., read_file, grep_search, search) is mentioned for comparison.

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