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 agentmods add skills/egeominotti/bunqueue/bunqueue-devnpx skills add egeominotti/bunqueue --skill bunqueue-devgit clone --depth 1 https://github.com/egeominotti/bunqueueWhat 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 | $0.00022 | $0.01033 |
| Opus 5 | $0.00011 | $0.00517 |
| Sonnet 5 | $0.00004 | $0.00207 |
| Haiku 4.5 | $0.00002 | $0.00103 |
Grade A, and why
bunqueue-dev 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 yesterday.
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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
bunqueue Development Guide
You are working on bunqueue, a high-performance job queue for Bun with SQLite persistence.
Architecture
bunqueue uses a sharded priority queue architecture:
- Shards: Auto-detected from CPU cores (power of 2, max 64). Jobs are assigned via
fnv1aHash(queue) & SHARD_MASK - Persistence: SQLite in WAL mode with a 10ms WriteBuffer for batching writes
- Transport: TCP (msgpack) on port 6789, HTTP on port 6790
- Two modes: Embedded (in-process) and TCP (client-server)
Request Flow
- PUSH: Client -> TcpPool -> TcpServer -> QueueManager -> Shard -> PriorityQueue -> WriteBuffer -> SQLite
- PULL: Client -> TcpServer -> QueueManager -> Shard -> PriorityQueue.pop()
- ACK: Client -> TcpServer -> AckBatcher -> Shard.complete() -> jobResults (LRU)
- FAIL: Client -> TcpServer -> Shard.fail() -> retry (backoff) OR -> DLQ
Directory Structure
src/
cli/ # CLI interface
client/ # SDK (Queue, Worker, FlowProducer, Bunqueue)
queue/ # Queue with DLQ, stall detection
worker/ # Worker with heartbeat, ack batching
tcp/ # Connection pool, reconnection
workflow/ # Workflow Engine (Workflow DSL, Engine, Executor, Store)
domain/ # Pure business logic
queue/ # Shard, PriorityQueue, DlqShard, UniqueKeyManager
application/ # Use cases and managers
operations/ # push, pull, ack, query, queueControl
infrastructure/ # Persistence, server, scheduler, backup
shared/ # Utilities (hash, lock, lru, skipList, minHeap)
Workflow Engine
Located in src/client/workflow/. Pure consumer layer on bunqueue (no core modifications).
- workflow.ts — Fluent DSL:
.step(),.branch(),.path(),.waitFor() - engine.ts — Public facade: register, start, signal, getExecution, close
- executor.ts — Core logic: step execution, branching, compensation, signals
- store.ts — SQLite persistence for execution state (workflow_executions table)
- types.ts — StepContext, Execution, StepJobData, EngineOptions, etc.
- Export:
import { Workflow, Engine } from 'bunqueue/workflow'
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.
- yesterday First seen · 96 lines · 22 tokens per session scan A 32dcc71a7784
bunqueue-dev is a skill published in the GitHub repository egeominotti/bunqueue (544 stars, last pushed yesterday), licensed MIT. It adds 22 tokens to every session and 1,033 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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