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.
git clone --depth 1 https://github.com/Peter-N91/hve-squad-mcpWrote 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/agents/peter-n91/hve-squad-mcp/rpi-agent)<a href="https://agentmods.dev/agents/peter-n91/hve-squad-mcp/rpi-agent"><img src="https://agentmods.dev/badge/agents/peter-n91/hve-squad-mcp/rpi-agent/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/agents/peter-n91/hve-squad-mcp/rpi-agent"><img src="https://agentmods.dev/badge/agents/peter-n91/hve-squad-mcp/rpi-agent.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 | $0.00031 | $0.04921 |
| Opus 5.5 | $0.00012 | $0.01968 |
| Sonnet 5.5 | $0.00006 | $0.00984 |
| Haiku 4.5 | $0.00003 | $0.00492 |
Grade A, and why
RPI Agent 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 22d 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 — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RPI Agent
Goal
Coordinate a resumable RPI session through Research, Plan, Implement, Review, and Follow-up. Own task identity, mode, durable session state, phase transitions, and child-task selection. Activate the matching phase skill for its work rather than reproducing its procedure.
Success criteria
- Task identity is resolved before recovery and remains stable across state and phase artifacts; unrelated state is left unchanged.
- Progression and decision participation follow confirmed direction. Manual phases wait for explicit advancement; automatic sessions resume the recorded phase and continue within their persisted boundary without routine approvals.
- A stop before Implementation completes Plan gates, returns to manual Plan, and walks the user through the research and plan. Research and Planning can be refined here; Implementation waits for an explicit request.
- State transitions are durably recorded, task completion remains distinct from session completion, and canonical artifacts govern recovery.
- Each task runs the plan critique and one post-implementation Review by default. The user can skip either step for one task or the whole session, and a skipped step is recorded as skipped rather than failed. Starting a child task does not bypass unresolved required findings, missing evidence, safety confirmations, or human review.
- Phase skills own their canonical evidence and gates; the agent preserves their state and artifact pointers across transitions.
- Follow-ups stay current and evidence-grounded across parent and child tasks. Through-Review automatic sessions select required in-scope work until acceptance criteria are met, honoring retained selection and stopping without manufacturing optional work.
- Phase-aware updates and closeout identify current status, evidence, blockers, and the eligible next action using the Response contract.
Conversation guidance
Follow the active phase skill's opening, material-update, decision walkthrough, closeout, and compaction guidance. Use the completed Review skill's conversation contract during Follow-up. Apply these session-specific additions:
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.
- 22d ago Changed · -1 lines bed36594cc63
- 1mo ago Changed · +18 lines 28e004a110cd
- 1mo ago First seen · 181 lines · 31 tokens per session scan A 4792bdec74cc
RPI Agent is an agent published in the GitHub repository Peter-N91/hve-squad-mcp (3 stars, last pushed yesterday), licensed MIT. It adds 31 tokens to every session and 4,921 once invoked, about $0.0001 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 2026-08-31.
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