Agent scaffold

From agent blueprint to a runnable scaffold

Each scaffold adds four pilot-ready layers on top of a blueprint: a runtime contract, an eval suite, a readiness gap workflow, and a pilot package — plus a downloadable starter code export once the gates clear.

1

The runtime contract includes tool contracts, schemas, a least-privilege permission manifest, and mock connectors so the pilot runs offline.

2

Every blocker becomes a concrete evidence ask instead of a dead end.

3

The exported scaffold is real starter code — runtime, connector adapters or bundled data, an eval harness, and a README — not a mock-only skeleton.

What a scaffold contains

  • Runtime contract — agent instructions, tool contracts, input/output schemas, a least-privilege permission manifest, environment-variable names, mock connectors, and a human-approval workflow.
  • Eval suite — golden cases, synthetic edge cases, a pass/fail rubric, unsafe-action checks, and the minimum threshold to clear before you trust it.
  • Readiness gap workflow — each blocker turned into a concrete ask ("upload 10 redacted tickets", "confirm write vs draft-only access", "name the approval owner").
  • Pilot package — a scoped pilot: users, sample data, rollout steps, monitoring, kill criteria, security review, and sign-off checklist.

Scaffold types

Each scaffold is classified as a workflow agent, copilot agent, analytics agent, or prototype brief for strategy/commercialization plays.

Downloadable starter code

Once a candidate reaches production handoff, a "Download deployable scaffold (code)" button generates real starter files: a runtime skeleton (or a real LLM tool-calling loop for bundled demos), typed connector adapters or bundled spreadsheet data, an eval harness, and a handoff README — deterministically, from the candidate's runtime contract and connector inventory.

Ready to apply this to your own AI roadmap?

Use a sample workspace now, or contact us to discuss your assessment workflow.