Second Opinions as Infrastructure

Ennodia convenes independent artificial intelligence (AI) panels for judgments that are too important for one model. It shows you exactly where they disagree.

Code review is the first strong use case, not the category. The core pattern is delegation to installed local agents with a visible trace. Compare turns multiple answers into a disagreement map and one usable result. The Judge maps the evidence, and the Result Advisor recommends the answer.

Three Patterns

Replicate

Send the same question to multiple agents, then compare the answers.

{
  "tool": "ennodia_run",
  "arguments": {
    "prompt": "Review this release plan. Name the highest-risk assumption first.",
    "mode": "parallel",
    "compare": true,
    "category": "general",
    "budget": {
      "maxChildTasks": 3
    }
  }
}

Use this when the question is coherent as one prompt but the cost of a missed issue is high.

Decompose

Split a broad review into focused slices, then combine the useful completed outputs.

{
  "tool": "ennodia_start_compositional",
  "arguments": {
    "prompt": "Decide whether this release is ready.",
    "slices": [
      { "id": "install", "prompt": "Audit install and first-run instructions." },
      { "id": "budget", "prompt": "Audit budget and latency expectations." },
      { "id": "security", "prompt": "Audit data governance and local execution claims." }
    ],
    "budget": {
      "maxChildTasks": 3
    }
  }
}

Poll the returned task IDs with ennodia_get_compositional_status, then pass the ready task IDs to ennodia_start_compare.

Red-Team

Fan out prompts that argue against a proposal from different angles.

{
  "tool": "ennodia_run",
  "arguments": {
    "prompt": "Argue against this migration plan. Focus on hidden coupling, rollout risk, and unverifiable assumptions.",
    "mode": "parallel",
    "compare": true,
    "category": "code"
  }
}

Use this when the primary agent has a plausible plan and you want independent pressure before committing.

Staging Pattern

For larger reviews, have the primary agent stage a folder containing the case file: relevant paths, screenshots, dataset summaries, contracts, or decision criteria. Then pass cwd to Ennodia so child agents can inspect the same local context independently. Keep staged material deliberate. Do not give every agent an unbounded workspace when a smaller evidence bundle will do.

Skills Carry Expertise

Use Agent Skills as reusable rubrics. A skill can define the review standard, expected evidence, output shape, and escalation rules. Ennodia installs bundled skills as harness-visible SKILL.md folders, then passes skill IDs through a run without inlining the full instructions into every prompt.

Examples

• Security threat models: replicate a threat review, then compare blind spots and contradictions.
• Contract comparison: decompose obligations, termination, liability, and data handling into focused slices.
• Pre-mortems: red-team a roadmap, launch, or migration plan before work starts.
• Exam or rubric QA: send the same staged rubric to multiple agents. Compare where their grading differs.

Honest Constraints

Ennodia supports careful review. A run usually takes minutes, not seconds. Compare adds two serial model passes after the child agents finish. Parallel review with Compare costs roughly N child runs, a Judge, and a Result Advisor.

Ennodia uses installed agent CLIs and local tools. It does not use specialist models for one domain. Ennodia supports decisions by showing evidence, disagreements, and uncertainty. It does not make regulated, legal, financial, medical, or operational decisions for the user.

For storage and data movement boundaries, read Data Governance.