Prompt Assembly Error Boundary Instrumentation Prompt

This prompt is for production engineers and AI operations teams who need to harden their prompt assembly pipeline against partial failures. The job-to-be-done is wrapping each assembly step—variable substitution, context injection, tool schema insertion, example selection—with error boundary markers that capture the failing component, the partial state of the prompt at failure, and the fallback behavior that was triggered. Without this instrumentation, a single failed retrieval call or a missing variable can produce a silently corrupted prompt that reaches the model, generating outputs that are expensive to debug and impossible to attribute to a root cause. The ideal user is an engineer who already has a working prompt assembly pipeline and needs to add production-grade observability before scaling to more users, more models, or higher-stakes tasks.

Use this prompt when your assembly pipeline has multiple stages that can fail independently—for example, a RAG system where retrieval might time out, a dynamic template where a feature flag might be undefined, or a multi-tenant system where user-specific context might be unavailable. The prompt template expects you to provide the assembly pipeline definition as a sequence of named steps, each with a function, expected inputs, and a fallback strategy. It then generates instrumented wrapper code that catches exceptions at each boundary, logs the failure with a trace ID, records the partial prompt state, and either applies the fallback or halts assembly with a structured error. Do not use this prompt for simple single-step prompt construction where there is no meaningful partial state to capture, or for pipelines where failures should always halt the entire request without fallback—in those cases, standard exception handling is sufficient and this instrumentation adds unnecessary complexity.

Before applying the output, verify that every assembly step in your pipeline is represented and that the generated error boundaries do not swallow exceptions that should propagate. The instrumentation should produce machine-parseable error records that your observability stack can ingest—if you lack structured logging or trace storage, add that infrastructure first. For high-risk domains such as healthcare or finance, ensure that fallback behavior never silently degrades to a less accurate prompt without surfacing the degradation to a human reviewer or an upstream circuit breaker. The next step after implementing these boundaries is to run the companion eval checks for error boundary coverage: inject failures at each step and confirm that the correct boundary captures the failure, logs the partial state, and triggers the expected fallback.

This template is designed to be placed as a wrapper around your existing prompt assembly logic. It instructs the system to execute assembly steps sequentially, and if any step fails, to halt, capture the failure metadata, and execute a predefined fallback. The primary goal is to prevent silent, malformed prompts from reaching the model, replacing them with a known-safe degraded state and a rich error trace for debugging.

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SYSTEM: You are a Prompt Assembly Error Boundary Controller. Your task is to execute the assembly steps defined in [ASSEMBLY_STEPS] in strict order. You must not proceed to a subsequent step if the current step fails.

INPUTS:
- [ASSEMBLY_STEPS]: An ordered list of assembly operations, each with an ID, a description, and a validation check.
- [FALLBACK_PROMPT]: A minimal, safe prompt to use if any assembly step fails.
- [TRACE_ID]: A unique identifier for this assembly attempt.

INSTRUCTIONS:
1. Initialize an empty assembly log with the [TRACE_ID] and a start timestamp.
2. For each step in [ASSEMBLY_STEPS]:
   a. Execute the step's operation.
   b. Run the step's validation check on the result.
   c. If validation passes, append a success record (step ID, status: 'PASS', timestamp) to the log and proceed.
   d. If validation fails, append a failure record (step ID, status: 'FAIL', error_message, partial_state, timestamp) to the log. Immediately stop all further assembly steps.
3. If all steps pass, append a final 'ASSEMBLY_COMPLETE' record to the log. The final output is the fully assembled prompt.
4. If any step failed, append a 'FALLBACK_TRIGGERED' record to the log. The final output is the [FALLBACK_PROMPT].

OUTPUT FORMAT: You must output a valid JSON object with two top-level keys:
- "assembly_log": An array of log records as described in the instructions.
- "final_prompt": The string content of either the fully assembled prompt or the fallback prompt.

CONSTRAINTS:
- Do not fabricate a successful assembly if a step failed.
- The "final_prompt" must be exactly the [FALLBACK_PROMPT] if any failure occurred.
- The "assembly_log" must contain the [TRACE_ID] in its first record.

To adapt this template, replace the placeholders with your specific pipeline logic. [ASSEMBLY_STEPS] should be a structured list of your actual assembly functions, such as "Fetch User Context" or "Inject Tool Schemas," each paired with a programmatic validation check. [FALLBACK_PROMPT] must be a static, tested prompt that can handle the user's request in a degraded but safe manner, like a simple instruction to ask the user to rephrase. [TRACE_ID] should be injected from your application's request context. After implementing, run this through your eval suite to ensure the JSON output is always parseable and that the fallback triggers correctly when simulated step failures are introduced.

This prompt is designed to sit as a wrapper around your existing prompt assembly pipeline, not as a standalone step. Before the final assembled prompt is sent to the model, you inject this instrumentation prompt as an outer boundary that captures the assembly state, step progression, and any failure metadata. The instrumentation prompt should be the last assembly step—applied after all other context packing, tool schema injection, and variable substitution is complete. It receives the partially or fully assembled prompt along with assembly pipeline metadata and produces a wrapped, traceable payload that includes error boundary markers, step completion status, and fallback indicators.

Wiring pattern: Implement this as a decorator function in your assembly pipeline. The function accepts three inputs: the current assembled prompt state, a pipeline step manifest (list of expected assembly steps with status), and any caught exception data. The instrumentation prompt is called in two scenarios: (1) success path—after all assembly steps complete, to stamp the final prompt with trace metadata; (2) failure path—inside a try/catch block, to capture which step failed, the partial state, and what fallback was triggered. Store the output in your request log alongside the model response. Validation: Before sending to the model, verify that the wrapped prompt contains the required boundary markers ([ERROR_BOUNDARY_START] and [ERROR_BOUNDARY_END]), a valid trace ID matching your system's format, and a step status block. If markers are missing or malformed, log a preflight failure and either retry the instrumentation step or fall back to a minimal safe prompt.

Model choice and retries: Use a fast, cheap model for this instrumentation step (e.g., GPT-4o-mini, Claude Haiku, or a local model) since the task is structural wrapping, not reasoning. Set a strict timeout of 2-3 seconds. If the instrumentation prompt fails or times out, do not block the main inference path—log the failure and send the uninstrumented prompt with a flag indicating missing trace metadata. Logging: Store the full instrumented prompt payload, trace ID, step status block, and any error boundary content in your observability system. Index by trace ID so operators can join prompt assembly logs with model response logs. Human review: Not required for routine assembly, but if the error boundary indicates a fallback was triggered, surface the partial state and fallback decision to an operations dashboard for post-hoc review. What to avoid: Do not use this prompt to modify the semantic content of the assembled prompt—it should only add boundary markers and metadata. Do not run this on every turn of a multi-turn conversation unless assembly state changes; instead, instrument only when the prompt is rebuilt.