cyberchef_entropy

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

With no annotations provided, the description must carry the full behavioral burden. It does this well by disclosing that the analysis is representation-calibrated, with explicit max entropy values for Hex (4.0 bits/char) and Base64 (6.0 bits/char), and that the tool classifies input types. The main gap is that the exact return format (e.g., numeric score, classification label, or both) is not stated.

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 two sentences with no filler. The first sentence states the core operation and purpose; the second adds the critical representation-specific detail. Every clause earns its place, and the most important information is front-loaded.

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?

For a single-parameter tool without an output schema, the description is largely complete: it explains what the tool does, the input data, and special representation behavior. The only notable omission is the exact shape of the result (e.g., does it return a number, a classification label, or both). This is a minor gap because the invocation itself is fully covered.

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 input schema already describes the single parameter, giving 100% coverage and setting a baseline of 3. The description adds useful semantics by indicating that representation matters: Hex and Base64 encodings receive calibrated analysis. This goes beyond the schema's generic 'data string or payload representation' phrasing and helps an agent understand how the input representation affects behavior.

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 opens with a specific verb and resource: 'Calculates the Shannon entropy (randomness in bits per symbol) of the input data.' It further clarifies the tool's analytical purpose by naming example outcomes (plaintext, compressed data, packed shellcode, high-entropy encrypted ciphertext). This clearly distinguishes it from the sibling CyberChef tools, which perform different operations like encoding, decoding, or hashing.

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 gives clear context for when to use the tool: to determine whether input data is plaintext, compressed, packed, or encrypted. It does not explicitly list alternative tools or exclusions, but given the specialized purpose and the sibling list, the intended usage is sufficiently clear. A small deduction for not explicitly stating when NOT to use it.

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