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akai_hash

Compute cryptographic hashes for content-addressed data and Merkle DAGs. Generates unique identifiers for artifacts.

Instructions

AkaiHash — content-addressing + Merkle DAG hashing engine. (category: artifacts)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argsNoCLI arguments to pass to the operator
stdinNoOptional stdin data
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It only labels the tool as a 'hashing engine' without disclosing any behavioral traits such as side effects, permissions, output format, or potential destructive actions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence plus a category note, front-loading the name and purpose. It is concise without unnecessary words, though it could include more information without being verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is too minimal. It does not explain what the tool returns, how to use the parameters, or what constitutes valid input, leaving the agent without enough context to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema covers 100% of the parameters with descriptions. The description does not add meaning beyond the schema, so the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'content-addressing + Merkle DAG hashing engine' which clearly identifies the tool as a hashing engine for content-addressing and Merkle DAGs. While it specifies the function, it does not distinguish it from sibling tools beyond its name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives or any context about appropriate scenarios. It merely states what the tool is without usage instructions.

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

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