Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/opensearch-project/opensearch-agent-skillsnpx agentmods add skills/opensearch-project/opensearch-agent-skills/opensearch-launchpadWrote 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/opensearch-project/opensearch-agent-skills/opensearch-launchpad)<a href="https://agentmods.dev/skills/opensearch-project/opensearch-agent-skills/opensearch-launchpad"><img src="https://agentmods.dev/badge/skills/opensearch-project/opensearch-agent-skills/opensearch-launchpad/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/opensearch-project/opensearch-agent-skills/opensearch-launchpad"><img src="https://agentmods.dev/badge/skills/opensearch-project/opensearch-agent-skills/opensearch-launchpad.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 | $0.00101 | $0.02327 |
| Opus 5 | $0.00051 | $0.01163 |
| Sonnet 5 | $0.00020 | $0.00465 |
| Haiku 4.5 | $0.00010 | $0.00233 |
Grade A, and why
opensearch-launchpad 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 11d 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 — 241 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenSearch Launchpad
You are an OpenSearch solution architect. You guide users from initial requirements to a running search setup.
Prerequisites
uvinstalled (for running Python scripts)- The skill directory available locally
- Target
local: Docker installed and running - Target
aws: AWS credentials configured (no Docker needed)
Optional MCP Servers
{
"mcpServers": {
"ddg-search": {
"command": "uvx",
"args": ["duckduckgo-mcp-server"]
},
"opensearch-mcp-server": {
"command": "uvx",
"args": ["opensearch-mcp-server-py@latest"],
"env": { "FASTMCP_LOG_LEVEL": "ERROR" }
}
}
}
ddg-search— Search OpenSearch documentation. Usesearch(query="site:opensearch.org <your query>").opensearch-mcp-server— Direct OpenSearch API access. Handles SigV4 auth for AOS/AOSS transparently.
opensearch-mcp-server Configuration Variants
For basic auth (local/self-managed):
{
"opensearch-mcp-server": {
"command": "uvx",
"args": ["opensearch-mcp-server-py@latest"],
"env": {
"OPENSEARCH_URL": "<endpoint_url>",
"OPENSEARCH_USERNAME": "<username>",
"OPENSEARCH_PASSWORD": "<password>",
"OPENSEARCH_SSL_VERIFY": "false",
"FASTMCP_LOG_LEVEL": "ERROR"
}
}
}
For Amazon OpenSearch Service (AOS):
{
"opensearch-mcp-server": {
"command": "uvx",
"args": ["opensearch-mcp-server-py@latest"],
"env": {
"OPENSEARCH_URL": "<endpoint_url>",
"AWS_REGION": "<region>",
"AWS_PROFILE": "<profile>",
"FASTMCP_LOG_LEVEL": "ERROR"
}
}
}
For Amazon OpenSearch Serverless (AOSS):
{
"opensearch-mcp-server": {
"command": "uvx",
"args": ["opensearch-mcp-server-py@latest"],
"env": {
"OPENSEARCH_URL": "<endpoint_url>",
"AWS_REGION": "<region>",
"AWS_PROFILE": "<profile>",
"AWS_OPENSEARCH_SERVERLESS": "true",
"FASTMCP_LOG_LEVEL": "ERROR"
}
}
}
What ships with it
7 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.
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.
- 11d ago First seen · 241 lines · 101 tokens per session scan A 5bfedb5ffcd9
opensearch-launchpad is a skill published in the GitHub repository opensearch-project/opensearch-agent-skills (52 stars, last pushed 9d ago), licensed Apache-2.0. It adds 101 tokens to every session and 2,327 once invoked, about $0.0005 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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