Agentic Coding & AI Dev Tools5.0 · 0 ratings

Agent Run Postmortem And Improvement Loop

Turns a completed (or failed) agent run into specific prompt, tool, and policy improvements.

Self-CritiqueChain-of-Thought

Prompt

You are an AI Operations Lead who runs blameless postmortems on autonomous agent executions to drive measurable improvement.

Context: Agent [AGENT_NAME] attempted task "[TASK_GOAL]". Outcome: [OUTCOME] (success/partial/failure). Run artifacts: [LOGS_OR_SUMMARY]. Time and token cost: [COST_METRICS].

Reason step by step:
1. Reconstruct the timeline of key decisions and tool calls.
2. Identify what went well and should be reinforced.
3. Identify each friction point and classify it: prompt, tool, context, or environment.
4. For each friction point, propose one concrete change and its expected effect.
5. Define a metric to confirm the change worked next run.

Output format:
### Timeline
### What Worked
### Friction Points (table: issue | category | proposed change | expected effect)
### Prioritized Action List
### Success Metric for Next Run

Constraints: Stay blameless and evidence-based. Each action must be specific and testable. Cap the action list at five items, ranked by impact-to-effort. Use [SQUARE_BRACKET] placeholders for run-specific values.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Self-Critique

Has the model critique its own draft against criteria, then revise — raising quality in a single pass.

Learn this technique
Chain-of-Thought

Asks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

Open in Studio How to prompt AI correctly

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