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inkog_deep_scan

Detects complex vulnerabilities and logic flaws in AI agents using advanced analysis, complementing pattern-based scanning. Scans specified paths, with results available after approximately 10 minutes.

Instructions

Inkog Deep scan for AI agents. Uses advanced analysis to detect complex vulnerabilities, logic flaws, and security issues that pattern-based scanning may miss. Requires the Inkog Deep role. IMPORTANT: Deep scans typically take around 10 minutes — inform the user before starting and let them know the scan is running.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesFile or directory path to scan
agent_nameNoAgent name for dashboard identification (auto-detected from path if not provided)
Behavior3/5

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

No annotations provided, so description carries full burden. Discloses scan duration (~10 minutes) and role requirement, but does not confirm read-only nature or potential side effects. While 'scan' implies non-destructive, explicit statement would improve transparency.

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?

Compact three-sentence description: purpose, capability, and key usage notes (role, duration). Front-loaded with core functionality, no redundant or filler content.

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?

Covers essential aspects for a scan tool: purpose, detection capability, prerequisites, and timely warning. Lacks mention of output format or result handling, but no output schema exists and siblings may follow common patterns.

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 coverage is 100% with clear descriptions for both parameters (path and agent_name). The description adds no additional semantic meaning beyond the schema, meeting the baseline expectation for high coverage.

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?

Clearly states it performs a deep scan using advanced analysis to detect complex vulnerabilities and logic flaws, distinguishing from pattern-based scanning. Explicitly requires the Inkog Deep role, differentiating from sibling tools like inkog_scan.

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?

Provides context for when to use (for complex issues) and prerequisites (requires Inkog Deep role). Includes important temporal information (10 minutes) and user communication requirement. However, does not explicitly state when not to use or compare to alternatives like inkog_scan for faster results.

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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