Idéal pour
- Partir d'un prompt structuré et réutilisable plutôt que d'une conversation vierge.
- Adapter le prompt à vos propres données tout en conservant l'intention d'origine.
- Les workflows liés à Software Development, Debug & Testing.
Exécuteur de boucle de code agentique
Remplir ce promptExécute une boucle de code agentique où la tâche, la méthode de vérification et le critère d’achèvement sont choisis indépendamment, en itérant jusqu’à ce que le contrôle externe réussisse.
Modèle de prompt
Execute the following task as an agentic loop. Do not ask for confirmation between iterations.
### TASK
Perform this action: {{Action: # Implement, Implement a new feature, Implement a missing function body, Write unit tests for existing code, # Fix, *Fix a failing test or bug, Fix all compiler warnings, Resolve linter violations, # Improve, Refactor without changing behavior, Optimize a slow code path, Migrate code to a newer API or framework version, Add missing error handling}}
### CONTEXT
{{Project Context: if used in an AI agent use the current project}}
### LOOP STRUCTURE
Repeat the following cycle:
1. ACT: Apply the smallest meaningful change toward the task.
2. VERIFY: Check the result using this method: {{Verification: # Automated, *Run the test suite, Compile or build the project, Run the linter and static analysis, Execute the script or program and inspect the output, Validate output against a schema or contract, # Manual proxy, Run a single reproduction case, Compare behavior before and after the change, Measure performance with a benchmark, Diff the output against a known-good reference}}
3. FEED BACK: If verification fails, take the raw error output (stack trace, test report, compiler message) unmodified into the next iteration. Do not summarize or interpret it before acting on it.
### COMPLETION CRITERION
Stop the loop only when this condition is met: {{Done When: *All tests pass with zero failures, Build succeeds with zero warnings, Linter reports zero violations, Program runs without exceptions on the given input, Output validates against the schema, Benchmark meets the target threshold, Reproduction case no longer fails, Behavior is identical before and after refactoring, All new code paths are covered by tests}}
### SAFEGUARDS
- Maximum {{Max Iterations:5}} iterations. If the limit is reached without success, stop and report the last error, what was attempted, and a hypothesis for the root cause.
- If the same error occurs in two consecutive iterations, stop immediately and report the stall instead of retrying.
- Touch only files required by the task.
### ADDITIONAL INFORMATION:
{{ Additional Information: none }}
After completion, summarize in 3 short bullet points: what was changed, how it was verified, and how many iterations were needed.
Guide du prompt
Comment l'utiliser
- Copiez le modèle de prompt complet.
- Remplacez chaque variable par votre propre contexte ou choisissez l'une des options suggérées.
- Collez le prompt complété dans ChatGPT, Claude, Gemini ou un autre assistant IA.
Variables de ce prompt
Action
# Implement, Implement a new feature, Implement a missing function body, Write unit tests for existing code, # Fix, Fix a failing test or bug, Fix all compiler warnings, Resolve linter violations
Project Context
if used in an AI agent use the current project
Verification
# Automated, Run the test suite, Compile or build the project, Run the linter and static analysis, Execute the script or program and inspect the output, Validate output against a schema or contract, # Manual proxy, Run a single reproduction case
Done When
All tests pass with zero failures, Build succeeds with zero warnings, Linter reports zero violations, Program runs without exceptions on the given input, Output validates against the schema, Benchmark meets the target threshold, Reproduction case no longer fails, Behavior is identical before and after refactoring
Max Iterations
5
Additional Information
none
Exemple de départ
Execute the following task as an agentic loop. Do not ask for confirmation between iterations. ### TASK Perform this action: # Implement ### CONTEXT if used in an AI agent use the current project ### LOOP STRUCTURE Repeat the following cycle: 1. ACT: Apply the smallest meaningful change toward the task. 2. VERIFY: Check the result using this method: # Automated 3. FEED BACK: If verification fails, take the raw error output (stack trace, test report, compiler message) unmodified into the next iteration. Do not summarize or interpret it before acting on it. ### COMPLETION CRITERION Stop the loop only when this condition is met: All tests pass with zero failures ### SAFEGUARDS - Maximum 5 iterations. If the limit is reached without success, stop and report the last error, what was attempted, and a hypothesis for the root cause. - If the same error occurs in two consecutive iterations...
Comment fonctionnent les variables
Syntaxe des variables
Les variables sont entourées de {{ et }} et suivent ce modèle :
{{variable name: option1, option2, option3 }}
Variables prédéfinies
Une sélection peut référencer une liste de variables prédéfinie à l'aide de crochets. Elles apparaissent en [orange] et fournissent des valeurs courantes comme des couleurs, des tons ou des langues.
{{Tone: [tones] }}
Listes de choix personnalisées
Vous pouvez aussi fournir une liste de choix en ligne, séparés par des virgules.
{{Format: bullet points, paragraphs, numbered list }}
Astuce : vous n'avez pas besoin de l'application PUCO pour utiliser ces prompts ! Copiez simplement le modèle et remplacez chaque section {{…}} par votre propre texte directement dans ChatGPT, Claude, Gemini ou tout autre assistant IA.