Inventory: Already-Written Long-Horizon "Super Prompts" — Business & Marketing Edition

Compiled 2026-10-03. A catalog of existing prompts/systems that keep AI agents working until the whole job is done, sorted by how close each gets to the research bar (see long-horizon-super-prompts-research.md for the bar). Verdicts: ✅ meets the bar (persistence paired with verification), ⚠️ persistence-only (risky), 🟩 single-shot business/marketing prompt (not truly long-horizon).

Honest headline: the published, working "nonstop" prompts are overwhelmingly coding prompts. True long-horizon marketing prompts barely exist — the closest are loop/goal guides written for marketers plus local skills. The Tier 1 engineering prompts transfer to marketing by changing the definition of done.

Tier 1 — True long-horizon "keep working until done" prompts (published, working)

1. Local: long-horizon-kit/ (ready-to-deploy) ✅

Path: ~/Documents/Default Project/long-horizon-kit/

• brief-template.md — 10-block pseudo-formal master brief
• prompts/01-single-agent.md — "Keep going until done" + count contract + paired gates
• prompts/02-orchestrator.md — parallel-workers root prompt
• prompts/03-worker-spec.md — four-part spawn spec
• prompts/04-verifier.md — fresh-context adversarial reviewer
• harness/01-loop.md — stop hooks, /goal, budget, gate integrity
• harness/02-progress-ledger.md — verified ledger re-injected each round
• qa/pre-launch-rubric.md + qa/red-team.md — 20/20 scorecard + 13 exploits patched
• Verdict: ✅ the only collection here already scored against the research bar. Directly adaptable to business/marketing by filling the definition-of-done.

2. Local: research-doc templates

• ~/Documents/Default Project/long-horizon-super-prompts-research.md §6 — master brief, orchestrator, worker spec, session-resume ritual (business-shaped: "every module, every endpoint, frozen check")
• ~/Documents/Default Project/long-horizon-prompting-research.md §9.2 — "keep going until the request is fully addressed" block
• Verdict: ✅

3. OpenAI canonical persistence blocks (GPT-5 → 5.6 prompting guides) ⚠️→✅

Source: developers.openai.com/cookbook (GPT-5 prompting guide, ~Aug 2025 onward)

• Core text: "You are an agent — please keep going until the user's query is completely resolved, before ending your turn… Never stop or hand back to the user when you encounter uncertainty — research or deduce the most reasonable approach and continue."
• GPT-5.1/5.2: named <solution_persistence> block — "persist until the task is fully handled end-to-end; do not stop at partial fixes or analysis." Plus stop-rule form "Only stop when all are true: …", scope discipline ("Do not expand the task beyond what the user asked"), and <high_risk_self_check>.
• GPT-5.5/5.6: outcome-first lean migration + layer-of-work discipline (research/design/implementation/review).
• Codex family: plan-closure rule — "reconcile every previously stated intention as Done, Blocked, or Cancelled. Do not end with in_progress/pending items."
• Verdict: ⚠️ alone; ✅ when paired with their stop conditions + rubric. The single most-copied persistence text on the internet.

4. Anthropic Ralph loop ⚠️→✅

Source: anthropic.com/research/long-running-Claude (2026)

• Invocation prompt: /ralph-loop:ralph-loop "Please keep working on the task until the success criterion of <X> is achieved." --max-iterations 20 --completion-promise "DONE"
• Mechanism: an outer for-loop kicks the agent back into context whenever it claims completion and asks "is it really done?" — the agent admits it's not up to spec and keeps working. Progress file + test oracle + agent prompt with clear rules.
• Verdict: ✅ pattern (verification gate is structural, in the loop) — this is the persistence-with-gate pairing done right, and it's free.

5. /goal — Codex / Claude Code / Hermes native command ✅

Sources: Medium "Goal-oriented execution loop" reproduction guide; Adnan Masood "/goal: The Quiet Slash Command" (2026-08-05)

• You write a completion condition; the agent loops until an independent evaluator/judge model that did not do the work confirms the condition is met.
• Evolved from the community Ralph-loop hack into a native primitive across three runtimes in 2026.
• The marketing angle: "The Marketer's Guide to Claude Code Goals and Loops" applies it to marketing with a safety valve — "or stop after 15 turns and tell me what's still outstanding" so a genuinely unsatisfiable goal doesn't spiral spending money.
• Verdict: ✅ — the cleanest "nonstop until done" primitive in current tools.

6. Claude Code /loop + nested verify-loop workflows ⚠️→✅

Sources: Claude Code docs; "The NEW Way to Use Claude Code in 2026 (Loops)" (YouTube); "designing loops" school (Peter Steinberger / Boris Cherny quotes, 2026)

• The viral loop pattern: "End to end, and don't stop me until you are done" → build → code-review loop "until zero findings" → lint/build loop "until everything is green" → browser-verify loop "screenshot every page and prove it works, preferably on a live page."
• Quote capturing the doctrine: "You shouldn't be prompting coding agents anymore. You should be designing loops that prompt your agents."
• Verdict: ✅ when each nested loop has a machine-checkable exit condition; ⚠️ if the exit is judged by the same agent. Directly transferable to marketing: content-batch loop until every asset passes brand QA, campaign loop until every channel is live and screenshot-verified.

7. GSD (Get Shit Done) — spec-driven meta-prompting system ✅

Source: github.com/gsd-build/get-shit-done (~58.9K stars)

• Full system: atomic plans executed in fresh context windows, /gsd-progress --next auto-figures out the next step, phase loop (discuss-phase → plan-phase → execute-phase → verify-work), /gsd-audit-milestone verifies all requirements shipped, append-only state files.
• Field report (HN): "GSD ran for hours to achieve the same thing" vs. 20 minutes for plan-mode MVP — hours because completeness is enforced.
• Verdict: ✅ — persistence lives in the state machine, not the prose. Works on 14 runtimes (Claude Code, Codex, OpenCode, Cursor…). Heaviest token consumer; needs a Max/API plan for full runs.

8. Leaked production agent-loop prompts (Manus, Cursor, Devin, Claude Code, Copilot) ⚠️

Sources:

• github.com/x1xhlol/system-prompts-and-models-of-ai-tools (134K+ stars, 28+ tools, updated 2026)
• github.com/jujumilk3/leaked-system-prompts (e.g. manus_20250310.md)
• github.com/asgeirtj/system_prompts_leaks (~68.7K stars), elder-plinius/CL4R1T4S (~50.8K), Piebald-AI/claude-code-system-prompts (~12.8K)
• Manus loop text (excerpt): "Iterate: Choose only one tool call per iteration, patiently repeat above steps until task completion… Enter idle state when all tasks are completed or user explicitly requests to stop" — planner module + event stream + milestone checklist.
• GitHub Copilot agent-mode reminder instructions: layered prompts with an embedded "keep working until done; don't freeze on uncertainty / action-first" reminder injected with every request; community-custom instruction: "Execute all steps sequentially without pausing for confirmation unless a critical error…"
• Verdict: ⚠️ as reference material — great for studying how real products phrase autonomy, but these are one-line exhortations without verification gates; the stop condition is a goal you pair with /goal or a judge.

9. Auto-GPT (the original nonstop prompt) ⚠️

Source: community.openai.com "Dissecting Auto-GPT's prompt"; the original GitHub prompt

• The archetype: goal → continuous self-prompting loop with memory, tasks list, and no human in the loop. Historically important; famously drifted and burned tokens — the cautionary tale that motivates the whole non-counting/verification literature.
• Verdict: ⚠️ — use for historical structure (task list + self-continuation), never verbatim.

10. Nate's Notebook — 12 long-running-agent design prompts (paywalled) ✅-ish

Source: natesnewsletter.substack.com "…+ 12 Prompts to Help Build Long-Running Agents Yourself" (2025-12-09, paid)

• Design-time prompts: State Persistence Analysis, View Compilation Design, Attention Budget Allocation, Summarization Schema Design, External Memory Architecture, Multi-Agent Scope Design, Failure Reflection System, Architecture Ceiling Test, Context Observability Audit, + non-tech version.
• Synthesizes Google ADK / ACE / Manus context-engineering papers.
• Verdict: ✅ but these design your harness rather than run the work; and it's behind a paywall.

Tier 2 — Business / marketing prompts & guides with long-horizon properties

11. "The Marketer's Guide to Claude Code Goals and Loops" ⚠️→✅ — the direct hit

Source: getmarketingwithai.substack.com/p/the-marketers-guide-to-claude-code-735

• Marketing-specific application of /goal (finish line → Claude works until verified) and /loop (recurring checks as inputs change: content decays, competitors reprice, campaigns drift).
• Includes the key safety instruction for marketing goals: append "or stop after 15 turns and tell me what's still outstanding" to prevent an unsatisfiable goal from spending money forever.
• The closest existing thing to what you asked for: a marketer's "work nonstop until done" prompt guide.

12. monday.com — 40 AI marketing workflows + prompt-to-agent escalation 🟩→⚠️

Source: monday.com/blog/ai-agents/ai-prompts-for-marketing (2026)

• 40 fill-in marketing prompts (launch timelines, battlecards, content calendars…) designed so any validated prompt can be "elevated into an always-on agent that runs 24/7."
• Verdict: 🟩 prompts individually; ⚠️ the escalation idea = persistence without a verification gate unless you add one.

13. Kieran Flanagan's marketing mega-prompts 🟩

Sources: LinkedIn/Dharmesh Shah post (Agent.ai version) + Kieran's 8-week AI marketing course prompt

• Prompt 1: prompt-library generator — reverse-engineers elite marketers' mental models for any discipline (SEO, Paid, Lifecycle) and outputs a full prompt library. Meta: it manufactures business super-prompts.
• Prompt 2: builds an entire 8-week AI marketing course with daily real deliverables, weekly capstones, CMO playbook actions — a large multi-deliverable artifact from one prompt (structured, but one-shot).
• Verdict: 🟩 large-scope, not agent-looped. Feed its output into a Tier-1 loop for true nonstop execution.

14. "1 prompt = $250K CMO" mega-prompt 🟩

Source: Medium (the-efficient-entrepreneur) "How 1 AI prompt does the work of a $250K CMO"

• Long role+context prompt: seasoned CMO, 15+ yrs, scaling $1M→$50M ARR, B2B/B2C/SaaS depth → strategy output.
• Verdict: 🟩 — rich role/context, zero persistence or verification. Typical of the viral genre.

15. Reddit viral whole-project prompts 🟩

• r/ChatGPTPromptGenius "This single prompt generates my entire MARKETING [plan]" — strategic plan + competitive analysis + ROI prediction + resource allocation
• r/ChatGPTPromptGenius "This ChatGPT Prompt Writes Your Entire Business Plan" — market analysis, financials, exec summary, marketing/sales strategy
• Verdict: 🟩 — "entire deliverable in one response" is the opposite of long-horizon agent work; useful only as the success-predicate source for a real brief.

16. Autonomous marketing platforms (prompts-as-goals) ⚠️

• ActiveCampaign Autonomous Marketing Platform — "just type your goal in plain language, agents take it from there" (platform, not a portable prompt)
• Lyzr "12 AI agents for marketing agencies" (goal-orientation doctrine: outcome in → steps figured out → runs workflow to completion)
• Gumloop "15 marketing AI agents" (instruction sets = agent definitions for workflows like viral-tweet mining, Reddit marketing)
• CDP.com deployment guide — phased autonomy with guardrails (advance only on evidence: pilot beats holdout for consecutive weeks)
• Verdict: ⚠️ platforms with goals baked in; the CDP guardrail pattern is the marketing analogue of our verification gate.

Tier 3 — Business/marketing prompt libraries (single-shot; the raw material, not the loop)

None of these are long-horizon. They generate individual artifacts. To make them "nonstop," wrap the artifact set in a Tier-1 brief: put all N deliverables in the backlog, define done per deliverable, add the ledger + loop.

Local business/marketing skills (already-written end-to-end pipelines)

Installed in ~/.claude/skills/ — these are complete workflows that run until a whole business project ships (closest local equivalents to "marketing super prompts"):

Gap note: these skills define what to do well, but most don't carry the four long-horizon load-bearing pieces (success predicate, non-counting list, artifact-predicate return, harness gate). The kit in long-horizon-kit/ wraps them.

Bottom line: what to actually use for business/marketing "nonstop" work

1. For a real project run: start from long-horizon-kit/prompts/01-single-agent.md + harness/01-loop.md (only ready-made set that pairs persistence with gates). Fill the definition-of-done with the marketing deliverable list.
2. For the finish-line primitive: use /goal with an independent judge (Codex/Claude Code/Hermes) — plus the marketer's safety clause "or stop after 15 turns and report what's outstanding."
3. For recurring marketing work: /loop on a fixed verification script (rank checks, brand QA, live-page screenshots) — per the Marketer's Guide.
4. For breadth of raw business prompts: the Tier-3 libraries (SPOTIO/Orbit/Consensus/Amplemarket) as deliverable generators inside the loop, not as the loop.
5. For studying real product phrasing: the leaked-repo collection (x1xhlol et al.) — Manus's "repeat until task completion" loop is the best non-coding reference.

The gap nobody has published yet: a pseudo-formal long-horizon brief written specifically for marketing outcomes (campaign shipped, pipeline moved) with a non-counting list for marketing near misses (a plan instead of shipped assets, "brand QA passed" self-certified, channels half-configured). The kit's refusal-list method is the fastest way to build one — ~30 minutes.