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MCP Vulnerability Reporting

by badchars

create_vulnerability_report

Creates standardized vulnerability reports with findings, recommendations, impacts, and reproduction steps, turning detected issues into actionable remediation guidance.

Instructions

Create a professional vulnerability report following the standardized template format.

IMPORTANT FOR AI - BE CONCISE AND BRIEF:

  1. OVERVIEW: 2-3 sentences explaining what this vulnerability type is and why it's dangerous

  2. FINDINGS: 2-3 sentences describing what you found in this specific instance

  3. RECOMMENDATIONS: 3-4 brief bullet points with bold headers (e.g., "- Input Validation: Sanitize all user inputs")

  4. IMPACTS: 2-3 brief bullet points with bold headers (e.g., "- Data Breach: Attackers could access sensitive data")

  5. REFERENCES (optional): 2-3 relevant OWASP/CWE links

KEEP IT SHORT - Focus on key points only. No long paragraphs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
impactsYesAI-GENERATED (2-3 ITEMS): Brief impact statements. Format: '- **Header**: One sentence'. Keep each under 20 words.
findingsYes
overviewYesAI-GENERATED (2-3 SENTENCES): Brief explanation of what this vulnerability type is and why it's dangerous. Keep it concise.
referencesNoAI-GENERATED (optional): Relevant references (OWASP, CWE, PortSwigger, etc.). If not provided, template defaults will be used.
vulnerabilityYes
recommendationsYesAI-GENERATED (3-4 ITEMS): Brief remediation steps. Format: '- **Header**: One sentence explanation'. Keep each under 20 words.
stepsToReproduceYesAI-GENERATED (4-6 BRIEF STEPS): Short, clear reproduction steps. One sentence per step.
Behavior2/5

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

No annotations are provided, so the description carries full burden. It does disclose that the AI should be concise and brief, and provides a template structure for generated fields, but it does not state whether the tool persists data, returns a report ID, or requires authentication. This leaves the agent without key behavioral expectations.

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 description is moderately sized and uses a numbered list for clarity. However, it duplicates much of the information already in the parameter schema, and the 'IMPORTANT FOR AI' repetition could be trimmed. It is structured but not maximally efficient.

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?

Given the tool's complexity (7 params, nested objects, no output schema), the description omits important contextual details such as return value, error conditions, or how it relates to the report lifecycle. It covers the content format for AI-generated fields but leaves the overall workflow unclear.

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 description coverage is 71%, and many parameter descriptions already contain length/format constraints. The main description largely reiterates these constraints (e.g., '2-3 sentences', '3-4 brief bullet points') without adding new syntax or type information. Thus it provides minimal added value beyond the schema.

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 begins with a clear verb-action: 'Create a professional vulnerability report following the standardized template format.' This clearly identifies the tool's purpose and distinguishes it from sibling tools like list_reports or export_report.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., needing browser_test_payload results), nor does it differentiate from sibling tools like add_evidence_to_report or get_report_template.

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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