Latitude is an open-source platform for monitoring AI agents by collecting execution traces, grouping failures, dispatching coding agents to make fixes, and replaying failures to verify them. Teams use it to observe agent behavior, investigate errors, and monitor whether fixes prevent regressions. The catalogue entries include skills, instructions, and an MCP server for working with Latitude.
Borrowing it
Nothing to install: this file belongs to latitude-dev/latitude-llm. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/latitude-dev/latitude-llm/development/.agents/skills/async-jobs-and-events/SKILL.mdgit clone --depth 1 https://github.com/latitude-dev/latitude-llmWrote 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/latitude-dev/latitude-llm/async-jobs-and-events)<a href="https://agentmods.dev/skills/latitude-dev/latitude-llm/async-jobs-and-events"><img src="https://agentmods.dev/badge/skills/latitude-dev/latitude-llm/async-jobs-and-events/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/latitude-dev/latitude-llm/async-jobs-and-events"><img src="https://agentmods.dev/badge/skills/latitude-dev/latitude-llm/async-jobs-and-events.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00028 | $0.02455 |
| Opus 5 | $0.00014 | $0.01228 |
| Sonnet 5 | $0.00006 | $0.00491 |
| Haiku 4.5 | $0.00003 | $0.00246 |
Grade A, and why
async-jobs-and-events 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.
How it starts
The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Background jobs, domain events, and side effects
When to use: Queues and workers, domain event publishers, async notifications or projections, or not doing that work inside HTTP handlers.
Side effects and eventing
- Domain code emits domain events through domain-level publisher abstractions (ports), not ad-hoc calls from use-cases to email/HTTP/Slack.
- Workers handle notifications, integrations, projections, and other I/O asynchronously.
- Do not orchestrate side effects (fan-out integrations, “fire and forget” HTTP, etc.) inside HTTP handlers — enqueue / publish and return.
Domain event naming and publisher–consumer decoupling
Domain events represent facts that happened — state transitions on an aggregate — not instructions for what should happen next. The publisher must never know or care which handlers are subscribed.
Rules
- Name events after what the aggregate did, not what consumers need to hear. Good:
ScoreCreated,ScoreStatusChanged. Bad:ScoreDraftSaved(named to route around a handler),ScoreReadyForDiscovery(named after a consumer concern). - Smell test: if you deleted every event handler, would you still emit this event because it describes a meaningfully different thing that happened? If the answer is no, the event is coupling in disguise.
- One canonical event per state transition. Do not split a single write operation into multiple event types to route to different handlers. If a score is written, emit
ScoreCreated— regardless of whether the score is a draft or published. - Consumers own their filtering logic. If a handler only cares about published scores, the handler checks the payload or re-fetches state and skips drafts. The publisher does not pre-filter by emitting different event names.
- Dedupe keys must not collide across lifecycle stages. If the same entity emits the same event at different lifecycle points (e.g., draft save then final publish), include the relevant discriminator in the dedupe key — not in the event name. Example:
issues:discovery:${scoreId}:${status}instead of splitting into separate event types. - Payload carries facts, not routing hints. Include the aggregate's current state (or the fields consumers might filter on) in the payload. Let consumers decide relevance from payload data.
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 · 125 lines · 28 tokens per session scan A 42d85f45734a
async-jobs-and-events is a skill published in the GitHub repository latitude-dev/latitude-llm (4,632 stars, last pushed today), licensed MIT. It adds 28 tokens to every session and 2,455 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
phoenix-cli-development
Design and implementation guide for the Phoenix CLI (px). Covers the noun-verb command structure, dual-audience design (humans and coding agents), Commander.js patterns, configuration resolution, output formats, exit codes, and conventions for adding or modifying commands. Triggers when working on phoenix-cli commands…
phoenix-graphql
Write efficient GraphQL queries against the Phoenix API. Load this skill in two cases: (1) before composing any non-trivial GraphQL query yourself for data analysis (via the phoenix-gql bash command) — it contains schema entrypoints and patterns that eliminate the need for introspection; (2) when the user asks for…
phoenix-otel-development
Guide for the phoenix-otel TypeScript package — OTel registration, stack-based global provider management, and provider lifecycle.
trulens-evaluation-setup
Configure feedback functions and selectors for TruLens evaluations.
trulens-instrumentation
Instrument LLM apps with TruLens OTEL-based tracing - from setup to debugging and optimization.
trulens-notebook-execution
Execute and display Jupyter notebooks for TruLens demos and quickstarts.