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vutiendat284

Web Pentest MCP Server

by vutiendat284

export_bugbounty_report

Generates a Markdown bug bounty triage report with cURL proof, terminal output, SHA-256 hashes, OWASP risk ratings, and VRT priorities for HackerOne, Bugcrowd, or client submission.

Instructions

Bug Bounty One-Shot Triage Reporter (Phase 3 Engine). T? ??ng xu?t b?o c?o l? h?ng chu?n Markdown ph?c v? n?p HackerOne, Bugcrowd ho?c b?n giao Kh?ch h?ng Doanh nghi?p:

  • B?ng ch?ng 3 t?ng: L?nh cURL 1 ch?m, ??u ra terminal th?, m? b?m SHA-256 ??i chi?u to?n v?n.

  • ??nh gi? x?p h?ng k?p (Dual-Rating): ?i?m r?i ro OWASP Risk Rating k?t h?p Bug Bounty VRT (P1 - P5).

  • C? ch? khuy?t thi?u IPOD (Missing Constant) v? h??ng d?n v? l?i r? r?ng.

Input Schema

NameRequiredDescriptionDefault
finding_idNo
program_idNo
target_urlNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose meaningful output behavior (SHA-256 verification, OWASP/VRT dual rating, remediation guidance), but it never says whether a file is written to disk or content is returned, whether an existing finding is required, or what happens if finding_id is null.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The bullet structure front-loads the purpose and each bullet is substantive. Yet the '(Phase 3 Engine)' label and the mojibake-encoded Vietnamese add noise, and the bullets describe report content rather than invocation guidance, so size is spent on the wrong dimension.

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 re-explained. But for a three-parameter tool with zero annotation coverage and zero schema descriptions, the description leaves the invocation model (which parameter triggers which report, side effects) undeclared, which is a material gap.

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

Parameters1/5

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

Schema description coverage is 0% across all three parameters, and the description never mentions finding_id, program_id, or target_url. Nothing explains what these optional parameters select or how the enum value 'default-program' behaves, so the gap is entirely uncompensated.

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?

The description states a specific verb and resource: it exports a Markdown-format vulnerability report, and explains the report's content (three-layer evidence, dual rating, remediation). It does not differentiate itself from siblings such as inspect_finding_or_evidence or get_pentest_dashboard, so an agent must infer which tool to pick.

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

Usage Guidelines3/5

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

Usage context is implied by 'Phase 3 Engine' and by the destinations listed (HackerOne, Bugcrowd, enterprise handoff). However, no explicit when-not-to-use rule or comparison to sibling tools is provided, leaving selection to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.