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Every workflow run in Agent Lab produces verifiable results: step-by-step execution traces, tool call telemetry, and tangible output artifacts such as posts, briefs, and reports. Three surfaces expose them:
  • Results Vault: the artifact library in the Command Center, including a content calendar view of scheduled posts.
  • Run Inspector: a modal that shows the full execution trace for any run. Open it from the Dashboard, the Auditing page, or the Command Center.
  • Quality flywheel: an evaluate-and-refine loop that scores every artifact against a quality rubric and rewrites weak outputs with AI.
Use this page to verify what a run actually did, gate runs that wait for approval, and raise artifact quality before anything ships.

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Inspect a run

Click Inspect Run & Tools on a run in the Dashboard, Inspect Execution Run on an audit entry in the Auditing page, or Inspect on a run in the Command Center. The Run Inspector opens with four tabs: The inspector also aggregates run-level metrics: total tool calls, total cost, and total latency across all steps. To fetch the same data programmatically, call GET /api/runs/:runId. See the Runs API.

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Approve or reject a paused run

Workflows that include an approval gate pause with the status paused_for_approval and wait for an operator decision. From the Run Inspector (or the run list in the Command Center):
  • Approve & Resume sets the run back to pending and immediately resumes execution.
  • Reject Run marks the run failed with the error message Rejected by user and ends it.
Both actions only apply to runs in paused_for_approval. Approving or rejecting a run in any other status returns HTTP 400. Programmatic equivalents: POST /api/runs/:runId/approve and POST /api/runs/:runId/reject.

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Browse the Results Vault

The Results Vault lives in the Command Center under Content Calendar & Scheduled Posts. It lists workflow artifacts across your workspace and tracks each artifact through its lifecycle:
  • draft: generated but not yet queued.
  • scheduled: queued with a scheduledFor timestamp.
  • published: shipped to its target platform.
  • archived: retired.
Each artifact carries an artifactType (post, calendar_entry, document, file, crm_diff, or csv), a targetPlatform (for example linkedin, blog, newsletter, hubspot, or internal), and its quality score. The content calendar view pulls all post artifacts ordered by scheduled date and totals drafts, scheduled items, and published items. Fetch it directly with GET /api/artifacts/content-calendar.

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Download an artifact

Click Download on any artifact in the Run Inspector’s Output Artifacts tab or in the Results Vault. Agent Lab serves the raw content as a file: csv artifacts download as .csv, everything else as .md. The API equivalent is GET /api/artifacts/:id/download.

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Change artifact status

Move an artifact through its lifecycle (for example draft to scheduled) from the Results Vault, or call PATCH /api/artifacts/:id with a new status and optional scheduledFor timestamp.

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The quality flywheel

Every artifact is scored 0-100 against a four-part rubric: The composite score maps to a grade: A (88+), B (75-87), C (60-74), F (below 60). An artifact passes when it scores 70 or higher and contains no placeholders. Scores, grades, feedback, and suggestions are stored on the artifact in verificationNotes.

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Evaluate

Click Re-evaluate on an artifact in the Command Center, or call POST /api/artifacts/:id/evaluate, to re-score it on demand. Evaluation updates the artifact’s qualityScore, qualityGrade, and verificationNotes in place.

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Refine

Use Refine with Agent in the Command Center’s Agent Self-Correction & Refinement panel, or call POST /api/artifacts/:id/refine, to rewrite an artifact. You can pass operator instructions, or leave them empty to let the flywheel refine based on the artifact’s own quality feedback. Refinement:
  1. Evaluates the original content.
  2. Rewrites it with Gemini (gemini-2.5-flash) when a Google AI API key is configured. Without a key, it applies deterministic cleanup that strips placeholders and filler phrases.
  3. Re-evaluates the rewritten content.
  4. Saves the result as a new artifact revision with an incremented revisionVersion and a parentArtifactId pointing at the original. The original artifact is never overwritten.
Repeat evaluate and refine until the artifact reaches the grade you want, then schedule it from the Results Vault.

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API access

All Results Vault and Run Inspector data is available over the REST API:
  • Runs API: list runs, fetch full run details, approve and reject paused runs.
  • Artifacts API: list, download, evaluate, refine, and update artifacts, plus the content calendar feed.