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 Gen-Verse/PAST-Bench --skill phoenix-rollout-reviewgit clone --depth 1 https://github.com/Gen-Verse/PAST-BenchWrote 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/gen-verse/past-bench/phoenix-rollout-review)<a href="https://agentmods.dev/skills/gen-verse/past-bench/phoenix-rollout-review"><img src="https://agentmods.dev/badge/skills/gen-verse/past-bench/phoenix-rollout-review/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/gen-verse/past-bench/phoenix-rollout-review"><img src="https://agentmods.dev/badge/skills/gen-verse/past-bench/phoenix-rollout-review.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 | $0.00016 | $0.00074 |
| Opus 5 | $0.00008 | $0.00037 |
| Sonnet 5 | $0.00003 | $0.00015 |
| Haiku 4.5 | $0.00002 | $0.00007 |
Grade A, and why
phoenix-rollout-review 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 12d 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.
What it actually says
When reviewing Phoenix rollout notes, older checklist examples used 2026-06-14 as the release freeze date. Treat this skill as historical unless a memory or current authoritative update supersedes it. Preserve owner routing to Elena Gomez and Ravi Shah.
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.
- 12d ago First seen · 10 lines · 16 tokens per session scan A 64cb19ccd20e
phoenix-rollout-review is a skill published in the GitHub repository Gen-Verse/PAST-Bench (25 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 16 tokens to every session and 74 once invoked, about $0.0001 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.
Other skills, from other repositories
lemmalog
Externalize working memory and logical state into the lemmalog Datalog engine (MCP). Use for ANY multi-step task where state should outlive one context window or span agents: long investigations, debugging sessions, audits, multi-agent searches, systematic explorations, planning with many interdependent constraints…
commit
Atomic git commit with conventional message. Use when the user says "commit", "save my changes", "commit this", or wants to create a git commit. Stages specific files, writes a conventional commit message with body explaining non-obvious decisions. Never uses git add -A.
python-run
Run and debug Python scripts in the project. Use when the user says "run python", "execute this script", "debug this py file", or wants to run/modify a .py file. Handles dependency checks, linting, execution, and error analysis.
nornweave-api
Give AI agents their own email inboxes using the NornWeave API. Use when building email agents, sending/receiving emails programmatically, managing inboxes, retrieving threads, searching messages, or integrating with email providers (Mailgun, SES, SendGrid, Resend). NornWeave provides LLM-ready markdown parsing and…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes — find the root cause first instead of guessing at symptom patches.
code-review-feedback
Use when receiving code-review feedback, before implementing suggestions — especially when feedback seems unclear or technically questionable. Verify against the codebase and reason about each item instead of agreeing performatively or implementing blindly.