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websex_angr_analyze

Analyze a workspace binary with the angr Python library to support authorized, scoped security engagements and vulnerability analysis.

Instructions

Analyze a workspace binary with the angr Python library.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
engagement_idYes
auto_load_libsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden, and it discloses almost nothing: no note that angr analysis is computationally expensive/long-running, no prerequisites (valid ELF/PE, 32/64-bit support), no permission or engagement requirements, no statement of what is produced. Only the implicit 'workspace binary' scoping constraint is communicated.

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?

A single short sentence with the core verb-resource-engine front-loaded and no wasted words. Its brevity reflects under-specification rather than tight editing, but structurally it is clean.

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?

An output schema exists, so return values need not be described. However, with zero annotation coverage, zero schema description coverage, and two required parameters, the description leaves an agent without the prerequisites, runtime cost, or parameter meaning needed to invoke this reliably.

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

Parameters2/5

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

Schema description coverage is 0% across all three parameters, so the description must compensate and it barely does. 'Workspace binary' hints that path resolves inside a workspace and that engagement_id scopes the operation, but auto_load_libs (default false) is left entirely unexplained despite materially changing angr's behavior.

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?

States a specific verb (Analyze) and resource (a workspace binary), and names the underlying engine (angr Python library), which signals symbolic execution/CFG analysis rather than the static dumping that siblings like objdump or strings perform. It does not explicitly differentiate itself from websex_ghidra, websex_radare2, or websex_objdump, but the engine name carries most of that distinction.

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?

There is no when-to-use guidance, no exclusions, and no mention of alternatives among the many binary-analysis siblings. An agent must infer that angr means symbolic execution and that heavy analysis is warranted; nothing in the text routes it there.

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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