Continuation Prompt Engineering
Continuation Prompt Engineering
Section titled “Continuation Prompt Engineering”Purpose
Section titled “Purpose”This document is the canonical reference for the Vox project’s continuation prompt — the structured instruction block entered periodically during long AI coding sessions to re-anchor the model’s attention, prevent premature completion, and maximize multi-agent throughput.
The Layered Defense Model
Section titled “The Layered Defense Model”The continuation prompt is one layer of a three-layer immune system. Each layer has distinct responsibilities — overlap is waste.
| Layer | Lives In | Enforced By | Covers |
|---|---|---|---|
| System rules | AGENTS.md + tool overlays (for example GEMINI.md) + <user_rules> | IDE injection (every turn) | Architecture pointers, secrets, SSOT locations, environment-specific shell discipline |
| Continuation prompt | Human-entered periodically | Attention recency window | Behavioral directives, parallelism, anti-skeleton interrogation, task-specific scope |
| CI gates | TOESTUB, completion-policy.v1.yaml, orchestrator PolicyEngine | vox ci completion-gates, vox stub-check, cargo test | Machine-verifiable constraints — stubs, empty bodies, victory claims, unwired modules |
What Goes Where (Decision Rules)
Section titled “What Goes Where (Decision Rules)”- If a constraint is verifiable by a tool → CI gate. Not the prompt.
- If a constraint is architectural/structural → AGENTS.md. Read once per session.
- If a constraint fights attention decay or shapes generation behavior → Continuation prompt.
- If a constraint is task-specific → Continuation prompt, parameterized per session.
Design Rationale
Section titled “Design Rationale”Why the prompt works the way it does
Section titled “Why the prompt works the way it does”Each section of the continuation prompt targets a specific failure mode documented in LLM code generation research (2025-2026):
| Prompt Section | Failure Mode Targeted | Research Basis |
|---|---|---|
<execution_engine> (DO NOT STOP) | Premature completion / early exit | Exploits recency bias to anchor final instructions (Liu et al., 2024). |
<behavior> (ACT DON’T NARRATE) | Token waste; sycophancy | Limits non-functional conversational filler (SycEval, 2025). |
<state_management> (Memory dump) | Attention decay; context rot | Mitigates “lost in the middle” token decay (Liu et al., 2024; extended 2025). |
<parallel> (Concurrency Fallbacks) | Serial bottleneck; state-bleed | Adapts LLM single-turn structural limits for horizontal throughput. |
<circuit_breaker> (Loop control) | Fix-forward infinite loops | Hard-stops an agent from making 3+ identical attempts, preventing token exhaustion. |
<verification> (Machine gates) | The “Ritual Trap” (LLM sycophancy) | Replaces checklist emulation with objective tool confirmation (SycEval, 2025). |
Why it’s a prompt and not just AGENTS.md
Section titled “Why it’s a prompt and not just AGENTS.md”AGENTS.md is injected at the start of the context window. After 50K+ tokens of
conversation, those instructions suffer ~30% attention degradation (“lost in the middle”
research, 2025). The continuation prompt exploits the recency bias — information at the
end of the context window gets disproportionate attention weight.
Additionally, behavioral directives like “ACT DON’T NARRATE” and “BATCH WORK” are generation-shaping instructions that affect token-by-token output. These work best when they’re the most recent instruction, not buried in a system prompt.
Why it uses XML tags
Section titled “Why it uses XML tags”- XML tags create strong semantic boundaries in the attention pattern
- Models trained on instruction data (Claude, GPT-4, Gemini) show measurably better adherence to instructions wrapped in XML vs. markdown headers
- Nested tags (
<prime_directive>inside<instructions>) create priority hierarchy that the model respects during generation
What NOT to put in the continuation prompt
Section titled “What NOT to put in the continuation prompt”- Architecture pointers (already in AGENTS.md, wasted tokens)
- Secret management rules (already in AGENTS.md)
- Specific file paths or CI command names (these belong in AGENTS.md or docs — the continuation prompt should reference the behavior not the tooling)
- Long explanations or rationale (the model doesn’t benefit from knowing why — it benefits from knowing what to do)
The Prompt
Section titled “The Prompt”The following is the canonical continuation prompt. Copy-paste it as-is between sessions
or when context is long. The [TASK_CONTEXT] block is the only part that changes per session.
<instructions><behavior>- CHAIN OF THOUGHT: Use `<thought>` blocks strictly to plan complex edits and parallel operations before execution. Think first, then act.- ACT, DON'T NARRATE: Outside of `<thought>`, invoke tools immediately. No conversational filler.- NO PLACEHOLDERS: Every edit must be structurally complete. If you write `todo!()`, `pass`, or `// implementation here`, you fail the integration constraint.- SCOPE LOCK: Never attempt to edit external dependencies, lock files, or vendored/generated code to fix local compilation issues. Always fix root causes at the local call site. Sibling workspace members/crates are explicitly in-scope.- WIRE IMMEDIATELY: Connect new code to existing systems instantly. Unused functions and dead modules are architectural regressions.</behavior>
<state_management>- PREVENT CONTEXT ROT: If a task requires more than 10 consecutive tool interactions without completion, dump context and next steps to an **ignored** scratch location: OS temp (`%TEMP%` / `std::env::temp_dir()`), repo `tmp/` if present, or another path already covered by root `.gitignore` (see [`docs/agents/governance.md`](../../agents/governance.md)) — avoid new dotfiles at repo root that are not ignored. After dumping state, re-read it and explicitly evaluate whether any circuit breaker condition is now met before continuing.- VERIFY BEFORE DESTROYING: Prove a variable, function, or file has zero usages via codebase-wide search before deleting or renaming it.</state_management>
<parallel>- NO NATIVE SUB-AGENTS: LLMs generate tokens sequentially. You do not have native autonomous sub-agents. You achieve the "parallel effect" purely via tool-call concurrency.- BULK DISCOVERY: Never read or search files serially. If you need to check 5 files, emit 5 `view_file` or `grep_search` tool calls simultaneously in one response turn.- BATCH EDITS: Never edit a file serially. Group intra-file modifications into single batched `multi_replace` blocks, and emit parallel single-replace tool calls only for disjoint files.- ASYNCHRONOUS TASKS: Send long-running terminal builds to the background. Continue discovering and planning independent semantic clusters while the command runs.- CONCURRENCY FALLBACK: If a batched tool call partially fails, process the successful results immediately and re-emit only the failed calls. Do not re-run successful calls. If the orchestrator limits tool calls per turn, prioritize the highest-information call first and chain the rest. Do not degrade to random serial ordering.</parallel>
<verification>- PROVE, DON'T CLAIM: Never deduce success via mental evaluation. You MUST execute the project's native verification (`cargo check`, `npm run build`, `pytest`, `go test`, etc.) and evaluate stdout.- FOUNDATIONS FIRST: Validate base abstractions and schemas via the local build system before extending higher-level API layers.- NO CHECKLIST RITUALS: Do not pad your response with a numbered checklist restating the work. Your successful tool execution is the only required proof of work.</verification>
<circuit_breaker>- COMPILER LOOP: If you attempt to fix the EXACT SAME logic or compilation error 3 times without a change in output, STOP. Summarize the failure and await human intervention.- READ LOOP: If you search or read the same files 3 times without writing code, you have lost context. STOP, summarize your confusion, and ask for a vector.- BUDGET EXHAUSTION: If you have consumed 15 consecutive tool interactions on a single sub-task without generating a green build or passing test, STOP and summarize.- CATASTROPHIC REGRESSION: If a single edit causes a massive surge in unrelated test failures, immediately revert that specific file edit before attempting to fix forward.</circuit_breaker></instructions>
<execution_engine>- DO NOT STOP: Execute ALL remaining steps from the user plan.- RELENTLESS: Do not pause to ask permission, summarize progress, or confirm direction mid-execution.- AFTER EVERY RESPONSE: State what remains briefly. Then KEEP GOING in your next action.</execution_engine>Vox-Specific Enhancements (Optional Append)
Section titled “Vox-Specific Enhancements (Optional Append)”When working specifically on the Vox codebase, append this tightly scoped block. It serves as a recency-bias reminder for critical Vox constraints that models often forget deep into a session. This section prevents attention decay of structural limits without dumping the entirety of AGENTS.md:
<vox_context><active_skill>- DYNAMIC INJECTION: The orchestrator will inject procedural workflows (e.g., `superpowers:test-driven-development`) here based on task state.- PRIORITY: If an active skill is present, its instructions supersede generic behavioral rules.</active_skill><anti_skeleton>- TOESTUB BLOCKERS: `stub/todo`, `stub/unimplemented`, `empty-body`, `victory-claim/premature`, `unwired/module`, `arch/god_object`, `arch/sprawl`.- VERIFY: RUN `vox stub-check --path <changed-dirs>` and evaluate the output before completing work. Error-severity findings are hard blockers.- COMPLETION POLICY: Review `contracts/operations/completion-policy.v1.yaml` (Tier A, B, and C skeleton detectors).</anti_skeleton><architecture_invariants>- SECRETS: Use `vox_secrets::resolve_secret(...)`. NEVER read raw `std::env::var`.- BOUNDARIES: No new `.py` files in `scripts/`. No new `pub` items in FROZEN modules.- LIMITS: God object = max 500 lines / 12 methods. Sprawl = max 20 files/dir. Refactor immediately if breached.</architecture_invariants><agentic_orchestration>- CONTEXT ENGINEERING: Extract narrow, highly-relevant data. Antigravity IDE and Cursor Composer both punish massive prompt dumps.- SHELL DISCIPLINE: Adhere to `GEMINI.md` (Antigravity overlay) for terminal shape. Decomposition is prioritized over shell pipeline cleverness.</agentic_orchestration></vox_context>Tool Name Substitution Note
Section titled “Tool Name Substitution Note”The continuation prompt intentionally uses generic tool names (e.g., view_file, grep_search, multi_replace). These must be substituted if the target orchestrator uses different internal tool names (e.g., Cursor vs. Antigravity vs. Windsurf).
Maintenance
Section titled “Maintenance”This document is the SSOT for continuation prompt design. When modifying:
- Update the prompt text in the code block above.
- Update the rationale table if adding/removing sections.
- Run
vox ci check-docs-ssotto verify links. - The prompt is versioned by
last_updatedin frontmatter. - Prompt Rotation: If a behavioral constraint is fully enforced by a CI gate with zero false negatives over 14 days, remove it from the continuation prompt to reclaim token budget.
References
Section titled “References”- Completion policy SSOT
- Governance / TOESTUB
- Doc-to-code acceptance checklist
- Prompt engineering, system prompts, document-skills, and SCIENTIA (research 2026)
- AGENTS.md (repo root) — system-level rules
- Attention decay / “lost in the middle” research (Liu et al., 2024; extended 2025)
- SycEval / RLHF sycophancy persistence benchmarks (2025)