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 Xiaoher-C/agentbnb --skill genesis-pulsegit clone --depth 1 https://github.com/Xiaoher-C/agentbnbWrote 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/xiaoher-c/agentbnb/genesis-pulse)<a href="https://agentmods.dev/skills/xiaoher-c/agentbnb/genesis-pulse"><img src="https://agentmods.dev/badge/skills/xiaoher-c/agentbnb/genesis-pulse/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/xiaoher-c/agentbnb/genesis-pulse"><img src="https://agentmods.dev/badge/skills/xiaoher-c/agentbnb/genesis-pulse.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 | $0.00033 | $0.01241 |
| Opus 5.5 | $0.00013 | $0.00496 |
| Sonnet 5.5 | $0.00007 | $0.00248 |
| Haiku 4.5 | $0.00003 | $0.00124 |
Grade A, and why
genesis-pulse scanned grade A with 1 finding 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 2mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s "{{hubUrl}}/api/providers/<your_owner>/reliability" | jq '.' How it starts
The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
genesis-pulse — Self-Reflection Engine
Purpose
Run at the start of every heartbeat cycle. Produce a PulseReport that all downstream skills read. Use Layer 0 (Haiku/Flash) only. This skill should consume < 2,000 tokens per run.
Procedure
Step 1 — Read current state (all Layer 0)
# Credit balance from AgentBnB
agentbnb status --json
# Recent task results from memory
memory_recall "task result" --category events --limit 10 --since 7d
# Recent feedback received
memory_recall "feedback received" --category events --limit 10 --since 7d
Step 2 — Calculate idle_rate
idle_rate = 1 - (active_execution_seconds_in_last_60min / 3600)
If no execution data available: assume idle_rate = 1.0 (safe default for new agents).
Step 3 — Compute fitness_score
Pull 7-day data from memory (category: patterns, tag: pulse-history):
task_success_rate_7d = successful_tasks / total_tasks (default 1.0 if no history)
credit_growth_rate_7d = (balance_now - balance_7d_ago) / max(balance_7d_ago, 1)
utilization_rate = 1 - idle_rate (how much of capacity was used productively)
feedback_avg_score = average of all received ratings (1-5, default 3.0)
fitness_score =
0.4 × task_success_rate_7d +
0.3 × clamp(credit_growth_rate_7d, -1, 1) × 0.5 + 0.15 + # normalized to 0-0.3 range
0.2 × utilization_rate +
0.1 × (feedback_avg_score / 5)
Step 4 — Produce PulseReport
Write as structured JSON to memory (category: patterns, tag: pulse-current, importance: 0.6):
{
"timestamp": "<ISO-8601>",
"generation": 1,
"credit_balance": <number>,
"idle_rate": <0.0-1.0>,
"active_skills": ["genesis-pulse", "genesis-trader", ...],
"recent_tasks_7d": <count>,
"recent_failures_7d": <count>,
"pending_incoming_requests": <count>,
"fitness_score": <0.0-1.0>,
"fitness_components": {
"task_success_rate_7d": <number>,
"credit_growth_rate_7d": <number>,
"utilization_rate": <number>,
"feedback_avg_score": <number>
},
"layer1_tokens_today": <count>,
"layer2_credits_today": <number>,
"alerts": [],
"self_summary": {
"capabilities": ["<skill_id_1>", "<skill_id_2>"],
"success_rate": <task_success_rate_7d>,
"credit_balance": <number>,
"total_completed": <lifetime execution count>,
"provider_number": <number>,
"reliability": {
"current_streak": <number>,
"repeat_hire_rate": <number>,
"avg_feedback": <feedback_avg_score>
}
}
}
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.
- 2mo ago First seen · 150 lines · 33 tokens per session scan A 8d3fe3dabce9
genesis-pulse is a skill published in the GitHub repository Xiaoher-C/agentbnb (33 stars, last pushed 4mo ago), licensed MIT. It adds 33 tokens to every session and 1,241 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
genesis-pulse compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| genesis-pulseXiaoher-C/agentbnb | Skill | 33 | 4mo ago | MIT | A | 33 | Claude Code, Codex |
| nsauditor-ainsasoft/nsauditor-ai-agent-skill | Skill | 4 | 3d ago | MIT | B | 242 | Claude Code |
| shiplogdevallibus/shiplog | Skill | 56 | 6mo ago | MIT | B | 46 | Claude Code |
| x-tweet-by-conversationbrowser-act/skills | Skill | 6.3k | 2d ago | MIT | A | 218 | Claude Code, Codex |
| pkf-writingPrismer-AI/PrismerCloud | Skill | 1.4k | 15d ago | MIT | A | 78 | Claude Code, Codex |
| render-3d-product-showcasegooseworks-ai/goose-skills | Skill | 1.3k | 10d ago | MIT | A | 159 | Claude Code, Codex |
| email-lifecycle-flow-writergooseworks-ai/goose-skills | Skill | 1.3k | 10d ago | MIT | A | 50 | Claude Code, Codex |