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 xyva-yuangui/XyvaClaw --skill proactive-agent-3.1.0git clone --depth 1 https://github.com/xyva-yuangui/XyvaClawWrote 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/xyva-yuangui/xyvaclaw/proactive-agent-3.1.0)<a href="https://agentmods.dev/skills/xyva-yuangui/xyvaclaw/proactive-agent-3.1.0"><img src="https://agentmods.dev/badge/skills/xyva-yuangui/xyvaclaw/proactive-agent-3.1.0/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/xyva-yuangui/xyvaclaw/proactive-agent-3.1.0"><img src="https://agentmods.dev/badge/skills/xyva-yuangui/xyvaclaw/proactive-agent-3.1.0.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 | $0.00014 | $0.00194 |
| Opus 5 | $0.00007 | $0.00097 |
| Sonnet 5 | $0.00003 | $0.00039 |
| Haiku 4.5 | $0.00001 | $0.00019 |
Grade A, and why
proactive-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 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
Proactive Agent
WAL, Working Buffer, Memory, Safety rules: see
AGENTS.md(authoritative). This skill only has incremental additions.
Key Additions (beyond AGENTS.md)
- Compaction Recovery protocol
- Autonomous vs Prompted Cron guidance
- Tool Migration Checklist
- Verify Implementation, Not Intent
Trigger
Always active as behavioral layer.
Full reference:
SKILL-REFERENCE.md
What ships with it
16 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- _meta.json 251 B
- assets/AGENTS.md 3.8 KB
- assets/HEARTBEAT.md 2.9 KB
- assets/MEMORY.md 836 B
- assets/ONBOARDING.md 2.4 KB
- assets/SOUL.md 1.9 KB
- assets/TOOLS.md 1.0 KB
- assets/USER.md 926 B
- examples/README.md 720 B
- references/onboarding-flow.md 4.0 KB
- references/security-patterns.md 3.0 KB
- scripts/check.py 976 B runs code
- scripts/security-audit.sh 4.0 KB runs code
- SKILL-REFERENCE.md 21 KB
- SKILL-v2.3-backup.md 20 KB
- SKILL-v3-draft.md 17 KB
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 · 29 lines · 14 tokens per session scan A 61c669194137
proactive-agent is a skill published in the GitHub repository xyva-yuangui/XyvaClaw (21 stars, last pushed 1mo ago), licensed MIT. It adds 14 tokens to every session and 194 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.
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