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generate_report

Generate professional penetration test reports from collected security findings, formatted to PTES and OWASP standards, with support for multiple report types and output formats.

Instructions

Generate a professional penetration test report.

Creates a comprehensive security assessment report from collected findings, formatted according to industry standards (PTES, OWASP).

Args: client_name: Name of the client organization. engagement_type: Type of test: 'blackbox', 'greybox', or 'whitebox'. scope: List of in-scope targets (IPs, domains, URLs). exclusions: List of explicitly excluded targets. engagement_dates: Testing period (e.g. "2026-02-15 to 2026-02-28"). findings: List of finding dicts from Tengu tools. executive_summary: Executive summary text (can be LLM-generated). conclusion: Report conclusion text. report_type: 'full', 'executive', 'technical', 'finding', or 'risk_matrix'. output_format: 'markdown', 'html', or 'pdf'. output_path: File path to save the report. If empty, returns content inline. tools_used: List of tool names used during the engagement.

Returns: Generated report content and metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scopeNo
findingsNo
conclusionNo
exclusionsNo
tools_usedNo
client_nameYes
output_pathNo
report_typeNofull
output_formatNomarkdown
engagement_typeNoblackbox
engagement_datesNo
executive_summaryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries the transparency burden. It discloses output behavior: formats (PTES/OWASP), output types (full/executive/etc.), and the output_path behavior returning content inline if empty. It does not mention overwrite behavior or external dependencies, but is reasonably transparent for a reporting tool.

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?

The description is well-structured with a clear one-line purpose, an Args list, and a Returns section. It is slightly verbose with phrases like 'professional' and 'comprehensive' adding little, but the layout is scannable and information-dense without redundancy.

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 covers all parameters, return value, and report variants. With an output schema present, the return metadata is likely further specified. It lacks explicit prerequisites or side-effect warnings, but given the tool's complexity and completeness of input documentation, it is sufficiently contextual.

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

Parameters5/5

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

The input schema has 0% description coverage, but the description's Args section provides explanations for all 12 parameters, including valid report_type and output_format values. This fully compensates for the schema's lack of descriptions and adds meaning beyond the property names.

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 it generates a professional penetration test report, with a specific verb ('generate') and resource ('penetration test report'). It distinguishes itself from sibling scanner and enumeration tools by focusing on report creation rather than data collection.

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?

The description implies usage after findings are collected, noting that 'findings' should be a list of finding dicts from Tengu tools. However, it does not explicitly state when not to use it or compare it to alternatives, though no sibling tool competes directly.

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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