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skvil_report

Report suspicious AI agent skills to Skvil admins for security review and potential certification revocation. Submit skill hash and reason for review.

Instructions

Report a suspicious or malicious AI agent skill to Skvil admins for review. Requires an API key (use skvil_register first). Reports are reviewed by admins and confirmed findings lead to certification revocation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hashYesSHA-256 composite hash of the skill (e.g. "sha256:4a2f8b...c81e")
reasonYesWhy this skill is suspicious (10-1000 characters)
detailsNoAdditional details or evidence (optional, max 5000 characters)

Implementation Reference

  • The skvil_report tool handler registered on the MCP server. Takes hash, reason, and optional details parameters, calls api.report(), and returns a formatted success response with report ID and status.
    // ── skvil_report ──────────────────────────────────────────────────────────
    server.tool(
      'skvil_report',
      'Report a suspicious or malicious AI agent skill to Skvil admins for review. ' +
        'Requires an API key (use skvil_register first). Reports are reviewed by ' +
        'admins and confirmed findings lead to certification revocation.',
      {
        hash: hashSchema,
        reason: z
          .string()
          .min(10)
          .max(1000)
          .describe('Why this skill is suspicious (10-1000 characters)'),
        details: z
          .string()
          .max(5000)
          .optional()
          .describe('Additional details or evidence (optional, max 5000 characters)'),
      },
      async ({ hash, reason, details }) => {
        try {
          const result = await api.report(hash, reason, details);
          return {
            content: [
              {
                type: 'text',
                text:
                  '**Report submitted successfully**\n\n' +
                  `- **Report ID:** ${result.report_id}\n` +
                  `- **Status:** ${result.status}\n` +
                  `- **Skill hash:** ${hash}\n\n` +
                  'A Skvil admin will review this report. If confirmed, the skill ' +
                  'will be flagged as malicious and any existing certification ' +
                  'will be revoked.',
              },
            ],
          };
        } catch (error) {
          return { content: [{ type: 'text', text: formatError('report', error) }], isError: true };
        }
      },
    );
  • Input validation schema for skvil_report: hash (SHA-256), reason (10-1000 chars), and optional details (max 5000 chars).
    {
      hash: hashSchema,
      reason: z
        .string()
        .min(10)
        .max(1000)
        .describe('Why this skill is suspicious (10-1000 characters)'),
      details: z
        .string()
        .max(5000)
        .optional()
        .describe('Additional details or evidence (optional, max 5000 characters)'),
    },
  • API function that sends a POST request to /report endpoint with the skill hash, reason, and optional details. Requires authentication.
    /** Report a suspicious skill. */
    export async function report(
      hash: string,
      reason: string,
      details?: string,
    ): Promise<ReportResponse> {
      const body: Record<string, string> = { composite_hash: hash, reason };
      if (details !== undefined) body.details = details;
      return request<ReportResponse>('POST', '/report', { body, auth: true });
    }
  • ReportResponse type definition containing report_id (number) and status (string).
    export interface ReportResponse {
      report_id: number;
      status: string;
    }
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: it's a write operation (reporting), requires authentication (API key via skvil_register), involves admin review, and has consequences (certification revocation). It doesn't mention rate limits or error handling, but covers the essential mutation and auth aspects well.

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 efficiently structured in three sentences: purpose, prerequisites, and outcome. Each sentence adds critical information without redundancy. It's front-loaded with the main action and appropriately concise for the tool's complexity.

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?

For a mutation tool with no annotations and no output schema, the description provides strong context: purpose, prerequisites, process, and consequences. It doesn't detail the response format or error cases, but given the schema's 100% coverage and the clear behavioral disclosure, it's largely complete. A minor gap in output specifics prevents a perfect score.

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 100%, so the schema already documents all parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain hash format or reason constraints). Baseline 3 is appropriate since the schema does the heavy lifting.

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 the specific action ('Report a suspicious or malicious AI agent skill') and the target resource ('to Skvil admins for review'), distinguishing it from siblings like skvil_catalog (list), skvil_verify (check), or skvil_register (register). It explicitly mentions the purpose of reporting for admin review and potential certification revocation.

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

Usage Guidelines5/5

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

The description provides explicit usage guidance: it states when to use ('Report a suspicious or malicious AI agent skill'), prerequisites ('Requires an API key (use skvil_register first)'), and the outcome ('Reports are reviewed by admins and confirmed findings lead to certification revocation'). This clearly differentiates it from other tools like skvil_scan or skvil_stats.

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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