Computes exact concrete inputs that reach a target branch in a binary using Z3 and angr, while pruning specified failure paths.
Uses Z3 SMT Theorem Prover and angr to solve for exact concrete inputs reaching target branches while pruning failure paths.
| Name | Required | Description | Default |
|---|---|---|---|
| binary_path | Yes | Path to binary | |
| input_length | No | Symbolic input length | |
| target_address | Yes | Hex address of target block | |
| avoid_addresses | No | Pruned addresses |
Changes observed during successful MCP inspections.
Input schema / properties / avoid_addresses / descriptionPrevious value: -"Error paths to avoid"New value: +"Pruned addresses"Input schema / properties / binary_path / descriptionPrevious value: -"Absolute path to binary"New value: +"Path to binary"Input schema / properties / input_length / defaultRemoved value: -32Input schema / properties / input_length / descriptionAdded value: +"Symbolic input length"Input schema / properties / target_address / descriptionPrevious value: -"Target hex address (e.g. '0x401820')"New value: +"Hex address of target block"v2.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral-disclosure burden. It usefully discloses the Z3/angr symbolic-execution approach, the concrete-input output goal, and failure-path pruning, but it omits important behavior such as timeouts, unsat/error handling, architecture constraints, and result format.
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 a single efficient sentence with no wasted text. It front-loads implementation names rather than the action, but remains compact and readable.
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 complex symbolic-execution tool with no annotations and no output schema, the definition is only minimally adequate. It covers the core purpose and schema parameters, but leaves result format, operational limits, and failure behavior under-specified.
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 100%, so the schema already documents all four parameters and the baseline is 3. The description loosely reinforces target_address and avoid_addresses via 'target branches' and 'pruning failure paths,' but adds no syntax, defaults, or constraints beyond the schema.
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 and resource: solving for exact concrete inputs that reach target branches. It is clear what the tool does, though it does not explicitly differentiate itself from siblings such as trace_symbolic_taint or unflatten_control_flow.
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 no explicit when-to-use guidance, prerequisites, or alternatives. The phrase 'while pruning failure paths' implies a use case, but an agent must infer when to choose this tool over related symbolic-execution tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.