jpegadv_chi_sliding

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

No annotations are provided, so the description carries the full burden. It describes the analysis process ('divides... runs chi-square pair analysis') and outputs, but does not disclose read-only nature, performance implications, or other behavioral traits beyond the core functionality.

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?

Three sentences, ~50 words, front-loaded with the main purpose. No unnecessary information; every sentence contributes to understanding the tool's function and output.

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?

The description states what the tool does and what it returns, which is adequate for a moderately complex steganalysis tool. However, it lacks detail on the output format (e.g., structure of p-values or detection results) that an agent might need to interpret the results.

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 100% with parameter descriptions. The description adds value by explaining how parameters are used in the algorithm ('configurable size', 'runs chi-square pair analysis on each window'), providing context beyond the schema's basic definitions.

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 'sliding window chi-square analysis over sequential DCT coefficients' and specifies the output ('per-window p-values and detection results'). This distinguishes it from siblings like 'img_chi_square' and other jpegadv tools by focusing on sliding window and DCT coefficients.

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?

No explicit guidance on when to use this tool versus alternatives like 'jpegadv_f5_detect' or 'jpegadv_jsteg_detect'. The phrase 'to map where embedding starts and stops' implies a specific use case but does not provide exclusions or context for selection.

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