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get_trust_signals

Read-onlyIdempotent

Aggregate non-CVE trust signals for a package—maintainer trust, OpenSSF Scorecard, quality metrics, and SLSA/Sigstore provenance—to deep-vet packages for hardened, regulated, or compliance-driven environments.

Instructions

One-call aggregate of ALL non-CVE supply-chain trust signals: maintainer trust (bus factor, ownership changes), OpenSSF Scorecard, quality (criticality, release velocity, publish security), and SLSA/Sigstore provenance. USE WHEN: deep-vetting a package beyond CVEs (hardened/regulated env, SBOM/compliance, small-pkg ownership review, choosing between healthy candidates). Runs 4 backend endpoints in parallel. RETURNS: {maintainer, scorecard, quality, provenance} — each may be null if its backend call failed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ecosystemYes
packageYes

Implementation Reference

  • Handler for the get_trust_signals tool. Fires 4 parallel backend API calls (maintainers, scorecard, quality, provenance) with error isolation (each failing call returns null). Returns aggregated {maintainer, scorecard, quality, provenance} object.
    case "get_trust_signals": {
      const pkg = args.package;
      const eco = args.ecosystem;
      const safe = (p) => gJ(p).catch(() => null);
      const [maintainer, scorecard, quality, provenance] = await Promise.all([
        safe(`/api/maintainers/${eco}/${pkg}`),
        safe(`/api/scorecard/${eco}/${pkg}`),
        safe(`/api/quality/${eco}/${pkg}`),
        safe(`/api/provenance/${eco}/${pkg}`),
      ]);
      return ok({ maintainer, scorecard, quality, provenance });
    }
  • Tool definition and inputSchema for get_trust_signals. Declares name, description, annotations (readOnlyHint, idempotentHint), and inputSchema requiring 'ecosystem' (enum from ECOSYSTEMS) and 'package' (string).
    // ── 7. Supply-chain deep signals ────────────────────────────────────
    {
      name: "get_trust_signals",
      description:
        "One-call aggregate of ALL non-CVE supply-chain trust signals: maintainer trust (bus factor, ownership changes), OpenSSF Scorecard, quality (criticality, release velocity, publish security), and SLSA/Sigstore provenance. USE WHEN: deep-vetting a package beyond CVEs (hardened/regulated env, SBOM/compliance, small-pkg ownership review, choosing between healthy candidates). Runs 4 backend endpoints in parallel. RETURNS: {maintainer, scorecard, quality, provenance} — each may be null if its backend call failed.",
      annotations: {
        title: "get_trust_signals",
        readOnlyHint: true,
        destructiveHint: false,
        idempotentHint: true,
        openWorldHint: true,
      },
      inputSchema: {
        type: "object",
        properties: {
          ecosystem: { type: "string", enum: ECOSYSTEMS },
          package: { type: "string" },
        },
        required: ["ecosystem", "package"],
      },
    },
  • The handleToolCall function is the central dispatcher where get_trust_signals is registered in the switch statement at line 749. It's exported and consumed by both index.js (stdio) and http-server.js (Streamable HTTP), which register it via CallToolRequestSchema.
    export async function handleToolCall(name, args) {
      // Tool-scoped helpers that auto-forward the MCP tool name to the backend
      // via X-MCP-Tool header (enriches api_usage.source = "mcp:<tool>").
      const gJ = (path) => getJson(path, name);
      const gT = (path) => getText(path, name);
      const pJ = (path, body) => postJson(path, body, name);
Behavior4/5

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

Annotations declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds useful behavioral context: it runs 4 backend endpoints in parallel and returns fields that may be null if a backend call fails. No contradiction.

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 concise and well-structured, using 'USE WHEN' and 'RETURNS' to organize usage and output. Every sentence adds value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description fully explains the return structure (maintainer, scorecard, quality, provenance) and notes potential nulls. It addresses the tool's complexity and backend parallelism, making it complete for an AI agent.

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 0%, so the description carries the burden. It mentions 'ecosystem' and 'package' as inputs but does not explain them beyond what the schema provides (ecosystem has enum in schema). The description lacks additional parameter details like format or examples, so it compensates only partially.

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 tool aggregates all non-CVE supply-chain trust signals, listing four categories (maintainer trust, OpenSSF Scorecard, quality, SLSA/Sigstore provenance). It distinguishes itself from sibling tools like get_vulnerabilities or check_package by focusing on trust signals beyond CVEs.

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

Usage Guidelines4/5

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

The description explicitly states 'USE WHEN: deep-vetting a package beyond CVEs' with specific scenarios (hardened/regulated env, SBOM/compliance, etc.). It does not provide when-not to use or explicitly name alternatives, but the context is clear.

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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