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agent_analyze

Plan and execute multi-step debugging analysis for open-ended reverse-engineering goals, then report findings. Use for tasks like locating unpacking loops or tracing execution.

Instructions

AUTONOMOUS ANALYSIS: Ask the AI agent to plan, execute, and report on a debugging goal. The agent runs a ReAct loop, calls multiple debugging skills, and returns findings. USE WHEN: open-ended exploration — 'find unpacking loop', 'identify anti-debug', 'trace execution from main'. DO NOT USE for single specific operations — call the dedicated tool instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalYesGoal in plain English. Be specific. Examples: 'Find all VirtualAlloc call sites and identify the unpacking loop', 'Locate anti-debug checks and suggest patches', 'Trace 50 instructions from RIP and summarize control flow'.
max_stepsNoMax reasoning steps. 5-10 focused, 15-25 exploration, 30+ complex.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoStructured result data (varies by tool)
errorNo
detailsNoDetailed text breakdown
successYes
summaryYesOne-line human-readable result
suggested_next_toolsNoTools recommended to call next based on this result
Behavior3/5

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

With no annotations provided, the description carries the behavioral disclosure burden. It discloses that the agent runs a ReAct loop, calls multiple debugging skills, and returns findings, which is useful. However, it does not mention potential side effects (e.g., whether it might write or patch memory), runtime expectations, or any safety limitations, leaving a transparency gap.

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 compact and front-loaded with 'AUTONOMOUS ANALYSIS.' It conveys purpose, behavioral model, and usage guidance in two sentences plus a USE WHEN/DO NOT USE section, with no redundant information.

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?

The description adequately covers the key aspects: what it does, when to use it, and what to expect behaviorally. An output schema exists, so return format is covered elsewhere. However, given its autonomous multi-step nature, a note about potential side effects or runtime length would improve completeness, but the current coverage is nearly sufficient.

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?

Both parameters have complete descriptions in the schema (100% coverage), including the max_steps guidance for focused vs. exploration scenarios. The tool description adds no additional parameter semantics beyond what the schema already provides, so the baseline of 3 applies.

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 uses specific verbs 'plan, execute, and report' and clearly identifies the resource as a 'debugging goal.' It also explicitly distinguishes itself from the many single-operation sibling tools by stating 'DO NOT USE for single specific operations — call the dedicated tool instead,' preventing confusion.

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

Usage Guidelines4/5

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

It provides explicit USE WHEN conditions with concrete examples ('find unpacking loop', 'identify anti-debug') and an explicit DO NOT USE condition with a pointer to use dedicated tools. However, it does not name a specific alternative tool, instead referring to a category ('dedicated tool'), which is slightly less concrete.

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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