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pentagonal_audit

Audit smart contract security using 8 specialized agents to detect vulnerabilities like reentrancy, flash loans, and access control issues, returning findings with severity ratings and line numbers.

Instructions

Run an 8-agent security pen test on a smart contract. Each agent specializes in a different attack vector: reentrancy, flash loans, access control, gas griefing, oracle manipulation, front-running, integer overflow, and economic exploits. Findings are returned with severity ratings and line numbers. New security rules are automatically learned from each audit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesThe full smart contract source code to audit
chainNoWhich blockchain the contract targetsethereum
use_learned_rulesNoUse previously learned security rules during the audit
Behavior4/5

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

With no annotations provided, the description carries the full burden. It effectively discloses key behavioral traits: the 8-agent specialization, that findings include severity ratings and line numbers, and that rules are learned automatically. However, it doesn't mention performance aspects like execution time or resource requirements.

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

Conciseness5/5

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

The description is front-loaded with the core purpose, followed by supporting details about agents and outputs. Every sentence adds value: the first defines the action, the second lists specializations, the third describes outputs, and the fourth explains rule learning. No wasted words.

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

Completeness4/5

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

Given the tool's complexity (multi-agent security testing) and no output schema, the description does well by specifying the attack vectors and output format (severity ratings, line numbers). However, it could better address error cases or limitations (e.g., contract size constraints).

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?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description doesn't add any parameter-specific details beyond what's in the schema (e.g., it doesn't explain code format or chain implications). Baseline 3 is appropriate when the schema does the heavy lifting.

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

Purpose5/5

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

The description clearly states the specific action ('Run an 8-agent security pen test') on a specific resource ('smart contract'), and distinguishes it from siblings by detailing the specialized attack vectors (reentrancy, flash loans, etc.). It goes beyond the tool name to explain the multi-agent approach and output format.

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

Usage Guidelines3/5

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

The description implies usage for smart contract security auditing but doesn't explicitly state when to use this tool versus alternatives like 'pentagonal_fix' or 'pentagonal_rules'. It mentions 'New security rules are automatically learned', which hints at iterative use, but lacks clear guidance on prerequisites or exclusions.

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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