Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add yeaight7/agent-powerups --skill persistent-completion-loopgit clone --depth 1 https://github.com/yeaight7/agent-powerupsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/yeaight7/agent-powerups/persistent-completion-loop)<a href="https://agentmods.dev/skills/yeaight7/agent-powerups/persistent-completion-loop"><img src="https://agentmods.dev/badge/skills/yeaight7/agent-powerups/persistent-completion-loop/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yeaight7/agent-powerups/persistent-completion-loop"><img src="https://agentmods.dev/badge/skills/yeaight7/agent-powerups/persistent-completion-loop.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00057 | $0.01310 |
| Opus 5.5 | $0.00023 | $0.00524 |
| Sonnet 5.5 | $0.00011 | $0.00262 |
| Haiku 4.5 | $0.00006 | $0.00131 |
Grade A, and why
persistent-completion-loop scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Persistent Completion Loop is a PRD-driven persistence loop that keeps working on a task until ALL user stories have passes: true and are reviewer-verified. It wraps parallel execution with session persistence, automatic retry on failure, structured story tracking, and mandatory verification before completion.
When to Use
- Task requires guaranteed completion with verification (not just "do your best")
- User says "don't stop", "must complete", "finish this", or "keep going until done"
- Work may span multiple iterations and needs persistence across retries
- Task benefits from structured PRD-driven execution with reviewer sign-off
Do Not Use When
- User wants a full autonomous pipeline from idea to code -- use autonomous delivery instead
- User wants to explore or plan before committing -- use the plan skill instead
- User wants a quick one-shot fix -- delegate directly to an executor agent
- User wants manual control over completion -- use parallel execution directly
Why This Exists
Complex tasks often fail silently: partial implementations get declared "done", tests get skipped, edge cases get forgotten. This skill prevents this by:
- Structuring work into discrete user stories with testable acceptance criteria
- Iterating story-by-story until each one passes
- Tracking progress and learnings across iterations
- Requiring fresh reviewer verification against specific acceptance criteria before completion
Inputs
- A task description
- Optional: an existing PRD file; if none exists, a scaffold is auto-generated and must be refined with task-specific stories and acceptance criteria
PRD Mode
A scaffold PRD file is auto-generated when the loop starts if none exists.
Startup gate: Always initialize and validate the PRD at startup.
Reviewer selection: The completion reviewer validates the stories, and the reviewer cannot be the same writer lane/agent that implemented the code.
Execution Policy
- Fire independent agent calls simultaneously -- never wait sequentially for independent work
- Use background execution for long operations (installs, builds, test suites)
- Always pass the
modelortierparameter explicitly when delegating to agents - Deliver the full implementation: no scope reduction, no partial completion, no deleting tests to make them pass
- Default-safe behaviors apply. Review before committing/pushing.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 126 lines · 57 tokens per session scan A d8231c516539
persistent-completion-loop is a skill published in the GitHub repository yeaight7/agent-powerups (6 stars, last pushed 19d ago), licensed Apache-2.0. It adds 57 tokens to every session and 1,310 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-14.
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