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 splunk/splunk-agent-skills --skill alerting-and-notable-workflowsgit clone --depth 1 https://github.com/splunk/splunk-agent-skillsWrote 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/splunk/splunk-agent-skills/alerting-and-notable-workflows)<a href="https://agentmods.dev/skills/splunk/splunk-agent-skills/alerting-and-notable-workflows"><img src="https://agentmods.dev/badge/skills/splunk/splunk-agent-skills/alerting-and-notable-workflows/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/splunk/splunk-agent-skills/alerting-and-notable-workflows"><img src="https://agentmods.dev/badge/skills/splunk/splunk-agent-skills/alerting-and-notable-workflows.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 | $0.00092 | $0.06052 |
| Opus 5.5 | $0.00037 | $0.02421 |
| Sonnet 5.5 | $0.00018 | $0.01210 |
| Haiku 4.5 | $0.00009 | $0.00605 |
Grade A, and why
alerting-and-notable-workflows 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 1mo 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 — 498 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Alerting and Notable Workflows
Assess whether a Splunk alert, scheduled-report action, or Enterprise Security finding/notable or risk workflow is ready and where an observed break belongs. This skill is advisory and non-mutating. It does not write searches, operate a Splunk deployment, change a response record, or treat documentation as proof of runtime behavior.
Prerequisites
Start with the user's requested decision and every supplied fact. Build a small evidence ledger using exactly:
[supplied]for a requirement or assertion from the user;[observed]for a value directly shown by a named UI view, job or scheduler record, action log, message, webhook response, or downstream receipt, with time window and environment;[inferred]for a bounded interpretation derived from labeled facts; and[unknown]for an absent, stale, contradictory, or inapplicable fact.
Copy every explicit known fact and every explicit unknown from the request into
the ledger before interpreting it. Do not silently drop a named discriminator
such as role, locale, exact version, version-specific defect status, entitlement,
backend state, owner, timing, or topology. An explicit unknown stays [unknown]
and appears again in the smallest-evidence or handoff section when it can change
the decision.
Record the exact product, Cloud or Enterprise deployment, product and app
version, premium app and entitlement evidence, topology when material, workflow
owner, response owner, requested outcome, and affected window. Mark missing
facts unknown; never infer a product, version, entitlement, provider boundary,
or root cause from an app name or historical resolution.
Preserve applicability facts explicitly supplied by the request. If it states
Splunk Cloud Platform, self-managed Splunk Enterprise, Enterprise Security, or
Mission Control, record that product/deployment as [supplied]; do not weaken
it to unknown merely because the exact release or entitlement is missing.
Keep only the absent field—such as exact version, premium entitlement, region,
or provider state—[unknown], and gate only the conclusion that depends on it.
Repeat that exact supplied product/deployment in both Applicability and the
terminal Ownership and handoff section. Use this form: Product/deployment: [supplied] <exact supplied product>; exact version: [supplied|unknown] ....
Before returning, scan the request for the literal product terms Splunk Cloud Platform, self-managed Splunk Enterprise, Splunk Enterprise Security, and
Mission Control. Copy every present term into those two sections. Never write
product/deployment: unknown when one of those terms is present; only the exact
version, entitlement, region, topology, or provider state may remain unknown.
What ships with it
1 file 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.
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.
- 1mo ago First seen · 498 lines · 92 tokens per session scan A 83c1269fb5ed
alerting-and-notable-workflows is a skill published in the GitHub repository splunk/splunk-agent-skills (62 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 92 tokens to every session and 6,052 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-09-12.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…