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CI-1T Prediction Stability Engine

generate_config

Generate CI-1T integration boilerplate for your chosen framework. Specify framework and use case to receive endpoints, score format, and step-by-step instruction for production-ready code.

Instructions

Generate CI-1T integration boilerplate for a specific framework or language — no API call, no auth, no credits. Response: { framework, use_case, api_base, endpoints, score_format, auth, cost, instruction }. The instruction field tells you how to produce complete, production-ready integration code for the user's stack.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
frameworkYesTarget framework or language (e.g. "fastapi", "express", "django", "flask", "nextjs", "python", "typescript", "go", "rust")
use_caseNoIntegration pattern: "single" for single-model monitoring, "fleet" for multi-model fleet evaluation, "guardrail" for CI-as-guardrail (reject/fallback when unstable)

Implementation Reference

  • src/index.ts:909-944 (registration)
    Tool registration for 'generate_config' — calls server.tool() with name 'generate_config', defines input schema (framework string, optional use_case enum), and provides a description. Registered as a local, no-auth utility tool.
    server.tool(
      "generate_config",
      "Generate CI-1T integration boilerplate for a specific framework or language — no API call, no auth, no credits. Response: { framework, use_case, api_base, endpoints, score_format, auth, cost, instruction }. The instruction field tells you how to produce complete, production-ready integration code for the user's stack.",
      {
        framework: z.string().min(1).max(50).describe('Target framework or language (e.g. "fastapi", "express", "django", "flask", "nextjs", "python", "typescript", "go", "rust")'),
        use_case: z.enum(["single", "fleet", "guardrail"]).optional().describe('Integration pattern: "single" for single-model monitoring, "fleet" for multi-model fleet evaluation, "guardrail" for CI-as-guardrail (reject/fallback when unstable)'),
      },
      async ({ framework, use_case }) => {
        const useCase = use_case || "single";
        return {
          content: [
            {
              type: "text" as const,
              text: JSON.stringify(
                {
                  framework,
                  use_case: useCase,
                  api_base: "https://collapseindex.org/api",
                  endpoints: {
                    evaluate: { method: "POST", path: "/api/evaluate", body: '{ "scores": [u16, ...] }' },
                    fleet_evaluate: { method: "POST", path: "/api/fleet-evaluate", body: '{ "nodes": [[u16, ...], ...] }' },
                    health: { method: "GET", path: "/health", url: `${BASE_URL}/health` },
                  },
                  score_format: "Q0.16 unsigned 16-bit integers (0-65535). Convert from float: Math.round(probability * 65535)",
                  auth: "X-API-Key header with ci_... key. Single credential for all endpoints.",
                  cost: "1 credit per episode (evaluate), 1 credit per episode per node (fleet-evaluate). 1,000 free credits on signup.",
                  instruction: `Generate a complete, production-ready ${framework} integration for CI-1T using the "${useCase}" pattern. Include: API client setup, score submission, result parsing, error handling with retries, credit tracking from response (credits_used, credits_remaining), and a working example. Use the real endpoint ${BASE_URL}/api.`,
                },
                null,
                2
              ),
            },
          ],
        };
      }
    );
  • The handler function for generate_config. Takes framework and use_case parameters, returns a JSON response with boilerplate integration info including API endpoints, score format, auth details, and a dynamic instruction field that tells the user to generate production-ready code for the specified framework/language.
    async ({ framework, use_case }) => {
      const useCase = use_case || "single";
      return {
        content: [
          {
            type: "text" as const,
            text: JSON.stringify(
              {
                framework,
                use_case: useCase,
                api_base: "https://collapseindex.org/api",
                endpoints: {
                  evaluate: { method: "POST", path: "/api/evaluate", body: '{ "scores": [u16, ...] }' },
                  fleet_evaluate: { method: "POST", path: "/api/fleet-evaluate", body: '{ "nodes": [[u16, ...], ...] }' },
                  health: { method: "GET", path: "/health", url: `${BASE_URL}/health` },
                },
                score_format: "Q0.16 unsigned 16-bit integers (0-65535). Convert from float: Math.round(probability * 65535)",
                auth: "X-API-Key header with ci_... key. Single credential for all endpoints.",
                cost: "1 credit per episode (evaluate), 1 credit per episode per node (fleet-evaluate). 1,000 free credits on signup.",
                instruction: `Generate a complete, production-ready ${framework} integration for CI-1T using the "${useCase}" pattern. Include: API client setup, score submission, result parsing, error handling with retries, credit tracking from response (credits_used, credits_remaining), and a working example. Use the real endpoint ${BASE_URL}/api.`,
              },
              null,
              2
            ),
          },
        ],
      };
    }
  • Input schema definition for the generate_config tool: 'framework' is a required string (1-50 chars, targeting framework/language), and 'use_case' is an optional enum of 'single'|'fleet'|'guardrail'.
    {
      framework: z.string().min(1).max(50).describe('Target framework or language (e.g. "fastapi", "express", "django", "flask", "nextjs", "python", "typescript", "go", "rust")'),
      use_case: z.enum(["single", "fleet", "guardrail"]).optional().describe('Integration pattern: "single" for single-model monitoring, "fleet" for multi-model fleet evaluation, "guardrail" for CI-as-guardrail (reject/fallback when unstable)'),
    },
Behavior3/5

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

No annotations provided, so description carries burden. It discloses that no API call, auth, or credits are involved, and that the instruction field guides code generation. However, it omits details like idempotency or side effects.

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?

Two sentences, front-loaded with purpose, no wasted words. Every sentence contributes value.

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?

No output schema, but description details response structure (fields). With only 2 parameters, coverage is good. Missing usage guidelines but otherwise complete for its simplicity.

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 baseline 3. Description adds 'no API call, no auth, no credits' which is not parameter-specific. Parameter descriptions in schema already cover framework examples and use_case enum values.

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 CI-1T integration boilerplate, specifies no API call, no auth, no credits, and outlines the response structure. It is distinct from siblings like evaluate or health.

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?

The description implies usage for generating boilerplate but lacks explicit when-to-use or alternatives. No exclusions or comparisons to other tools are provided.

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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