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bigbang_validate

Validate a Big Bang values.yaml against DoD IL compliance requirements. Get compliance score, violations, and hardened values.

Instructions

Validate a Platform One Big Bang values.yaml against DoD IL compliance requirements. Returns compliance score, specific violations, and hardened values.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valuesYamlYesPaste your values.yaml content
targetLevelNoIL compliance target (default: il4)
bigbangVersionNoBig Bang version e.g. "2.31.0"

Implementation Reference

  • The handler function `handleBigbangValidate` that executes the Big Bang validation tool logic. It calls `runTool` with the Zod schema, validates the prompt via the Anthropic API using the Platform One system prompt, and returns the AI-generated compliance response.
    export async function handleBigbangValidate(args: unknown): Promise<string> {
      return runTool('bigbang_validate', args, Schema, async ({ valuesYaml, targetLevel, bigbangVersion }) => {
        const response = await anthropic.messages.create({
          model: MODEL,
          max_tokens: getTokenBudget('bigbang_validate'),
          system: PLATFORM_ONE_SYSTEM,
          messages: [
            {
              role: 'user',
              content: `Validate this Big Bang values.yaml for ${targetLevel} compliance.
    ${bigbangVersion ? `Big Bang Version: ${bigbangVersion}` : ''}
    
    \`\`\`yaml
    ${valuesYaml}
    \`\`\`
    
    Provide:
    1. **IL Compliance Score** (0-100) with scoring breakdown
    2. **Critical Violations** (blocking deployment approval at ${targetLevel})
       - Non-Iron Bank images (must use registry1.dso.mil)
       - Disabled required security addons
       - mTLS not enforced
       - Network policies missing
       - Insecure default credentials not rotated
    3. **Image Policy Violations** — list each non-IB image with its Iron Bank replacement path
    4. **Missing Required Addons** for ${targetLevel} with justification
    5. **Network Policy Gaps** (Istio, NetworkPolicy, Calico)
    6. **mTLS Configuration Issues** (Istio PeerAuthentication)
    7. **Hardened values.yaml** with ALL violations corrected
    8. **Line references** from the original values pointing to specific violations
    
    Reference specific Iron Bank image paths (registry1.dso.mil/ironbank/...) for all replacements.`,
            },
          ],
        });
    
        return response.content[0].type === 'text' ? response.content[0].text : '';
      });
    }
  • Tool definition object `bigbangValidateTool` including name 'bigbang_validate', description, and inputSchema (object with valuesYaml, targetLevel enum il2/il4/il5, bigbangVersion).
    export const bigbangValidateTool = {
      name: 'bigbang_validate',
      description:
        'Validate a Platform One Big Bang values.yaml against DoD IL compliance requirements. Returns compliance score, specific violations, and hardened values.',
      inputSchema: {
        type: 'object' as const,
        properties: {
          valuesYaml: { type: 'string', description: 'Paste your values.yaml content' },
          targetLevel: {
            type: 'string',
            enum: ['il2', 'il4', 'il5'],
            description: 'IL compliance target (default: il4)',
          },
          bigbangVersion: { type: 'string', description: 'Big Bang version e.g. "2.31.0"' },
        },
        required: ['valuesYaml'],
      },
    };
  • Zod validation schema that enforces valuesYaml as string (1-20000 chars), targetLevel as enum defaulting to 'il4', and optional bigbangVersion up to 500 chars.
    const Schema = z.object({
      valuesYaml: z.string().min(1).max(20000),
      targetLevel: z.enum(['il2', 'il4', 'il5']).default('il4'),
      bigbangVersion: z.string().max(500).optional(),
    });
  • Import of `bigbangValidateTool` and `handleBigbangValidate` from the implementation file.
    import { bigbangValidateTool, handleBigbangValidate } from './platform-one/bigbang-validate.js';
  • Registration of `bigbangValidateTool` in the `allTools` array for MCP tool listing.
    bigbangValidateTool,
  • Routing: case 'bigbang_validate' in handleToolCall switch statement dispatches to `handleBigbangValidate(args)`.
    case 'bigbang_validate':      return handleBigbangValidate(args);
  • Token budget configuration: bigbang_validate gets 3072 max_tokens.
    bigbang_validate: 3072,
  • Timeout configuration: bigbang_validate gets 30000ms timeout.
    bigbang_validate: 30000,
  • Response quality validation: bigbang_validate minimum length of 300 characters.
    bigbang_validate: 300,
Behavior4/5

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

No annotations provided, so the description carries the full burden. It clearly states the tool returns compliance score, violations, and hardened values. However, it does not explicitly state that the tool is read-only or describe any side effects, which would be helpful for a validation tool.

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?

A single sentence that effectively conveys purpose and output. No wasted words, information is front-loaded.

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 tool with 3 parameters and no output schema, the description covers the main purpose and return values. However, it could benefit from mentioning that the tool is read-only or providing a brief example of the output structure.

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%, so the baseline is 3. The description does not add significant meaning beyond what the parameter descriptions already provide. It mentions return types but not how parameters influence behavior.

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 the verb 'Validate' and the resource 'Platform One Big Bang values.yaml' against DoD IL compliance. Also specifies the return type (compliance score, violations, hardened values), distinguishing it from sibling tools like bigbang_harden.

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?

Implies usage for validating values.yaml before hardening, but no explicit guidance on when to use this tool versus its sibling bigbang_harden or others. Lacks exclusion statements.

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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