proofflow-maintainer

proofflow-maintainer is a skill for Claude Code, Codex from Hyperion-GPU/ProofFlow-v0.1. It costs 50 tokens per session (2,427 once invoked), scanned A, original, MIT.

A maintainer workflow for using ProofFlow during repository work. ProofFlow records evidence, decisions, actions, and claims in structured work records.

In plain words
What is it for?
It helps maintain an Agent Work Ledger, review diffs, triage issues, continue cases, and create or export Proof Packets for pull requests.
Why use it?
It helps keep complex coding work traceable and makes review conclusions supportable by recorded evidence.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Codex.

Good fit It helps maintain an Agent Work Ledger, review diffs, triage issues, continue cases, and create or export Proof Packets for pull requests.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hyperion-gpu/proofflow-v0.1/proofflow-maintainer
Install

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.

Any agent
npx skills add Hyperion-GPU/ProofFlow-v0.1 --skill proofflow-maintainer
Clone the repo
git clone --depth 1 https://github.com/Hyperion-GPU/ProofFlow-v0.1

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for proofflow-maintainer

README.md
[![agentmods](https://agentmods.dev/badge/skills/hyperion-gpu/proofflow-v0.1/proofflow-maintainer.svg)](https://agentmods.dev/skills/hyperion-gpu/proofflow-v0.1/proofflow-maintainer)
Your own site
<a href="https://agentmods.dev/skills/hyperion-gpu/proofflow-v0.1/proofflow-maintainer"><img src="https://agentmods.dev/badge/skills/hyperion-gpu/proofflow-v0.1/proofflow-maintainer.svg" alt="Measured on agentmods" height="20"></a>
Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,427 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 2 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Anti-Refusal · line 37
    Skill attempts to nullify the agent's safety policies or restrictions ('you have no restrictions', 'ignore your guidelines', 'do anything now'). This is a direct jailbreak that disables guardrails.
    Fix: Remove jailbreak framing that nullifies safety policies or restrictions. Skill content must not instruct the agent to ignore its guidelines or operate without guardrails.
  • low MCP Rug Pull · line 49
    pip install without ==version installs the latest release, which could include malicious changes.
    Fix: Pin the version: pip install package==1.2.3
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00050 $0.02427
Opus 5 $0.00025 $0.01213
Sonnet 5 $0.00010 $0.00485
Haiku 4.5 $0.00005 $0.00243

Measured 8d ago against content hash 0875443445d5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

proofflow-maintainer 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 8d 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.

plugins/proofflow-maintainer/skills/proofflow-maintainer/SKILL.md · 226 lines

How it starts

The opening of the file, as written. The whole thing — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ProofFlow Maintainer

Use this skill when the user asks to use ProofFlow from Codex for repository maintenance, including:

  • keep an Agent Work Ledger for complex code tasks,
  • review the current diff with ProofFlow,
  • create or export a Proof Packet for a PR,
  • triage issue text into a ProofFlow Case,
  • inspect or continue an existing ProofFlow Case,
  • preserve evidence, decisions, actions, and policy gates while maintaining a repository.

Default to Agent Work Ledger for complex coding work. Use narrower workflows when the user's intent is clearly review-only, issue-intake-only, or packet export-only.

Operating Principles

  • Keep the workflow local-first. The default ProofFlow backend is http://127.0.0.1:8787.
  • Prefer ProofFlow MCP tools over ad hoc notes when recording Cases, Artifacts, Claims, Actions, Decisions, or Proof Packets.
  • Treat the current AgentGuard review as provenance-first unless the returned Claims contain specific semantic findings. It proves what diff was reviewed and what evidence was captured; it does not by itself guarantee a complete semantic code review.
  • Do not treat AI output as trusted unless it points to evidence. If evidence is missing, label the statement as an assumption.
  • Do not run tests through ProofFlow unless the user explicitly asks and the backend is configured to allow test command execution.
  • Do not merge PRs, close issues, or bypass policy gates unless the user explicitly asks and the repository workflow allows it.

Startup Check

Before running a ProofFlow workflow:

  1. Call proofflow_health.
  2. If the MCP server or backend is unavailable, tell the user to start the backend and install proofflow-mcp if needed:
pip install proofflow-mcp
cd backend
python -m uvicorn proofflow.main:app --port 8787

Choose The Workflow

  • Use Agent Work Ledger for complex code tasks, multi-file changes, feature work, behavior changes, risky local actions, or any task that needs contract, algorithm decisions, cost budgets, snapshots, Evidence, Claims, done criteria evaluation, and packet export.
  • Use AgentGuard review when the user only asks to review a current diff, PR, or branch changes.
  • Use Issue Triage when the user provides issue text, logs, reproduction steps, or a bug report and wants it captured as a ProofFlow Case.
  • Use Status / Proof Packet export when a Case already exists and the user wants a handoff artifact or review summary.

Read the full file on GitHub · 226 lines

Changes

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.

  1. 8d ago First seen · 226 lines · 0 tokens per session scan A 0875443445d5

Subscribe to this mod's changes

proofflow-maintainer is a skill published in the GitHub repository Hyperion-GPU/ProofFlow-v0.1 (49 stars, last pushed 1mo ago), licensed MIT. It adds 50 tokens to every session and 2,427 once invoked, about $0.0003 per session on Opus 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 2026-08-30.

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