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 personamanagmentlayer/pcl --skill elasticsearch-expertgit clone --depth 1 https://github.com/personamanagmentlayer/pclWrote 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/personamanagmentlayer/pcl/elasticsearch-expert)<a href="https://agentmods.dev/skills/personamanagmentlayer/pcl/elasticsearch-expert"><img src="https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/elasticsearch-expert/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/personamanagmentlayer/pcl/elasticsearch-expert"><img src="https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/elasticsearch-expert.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 | $0.00041 | $0.00968 |
| Opus 5 | $0.00020 | $0.00484 |
| Sonnet 5 | $0.00008 | $0.00194 |
| Haiku 4.5 | $0.00004 | $0.00097 |
Grade A, and why
elasticsearch-expert 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 7d 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 — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Elasticsearch Expert
Expert guidance for Elasticsearch, search optimization, ELK stack, and distributed search systems.
Core Concepts
- Full-text search and inverted indexes
- Document-oriented storage
- RESTful API
- Distributed architecture with sharding
- ELK stack (Elasticsearch, Logstash, Kibana)
- Aggregations and analytics
Index Management
from elasticsearch import Elasticsearch
es = Elasticsearch(['http://localhost:9200'])
# Create index with mapping
mapping = {
"mappings": {
"properties": {
"title": {"type": "text", "analyzer": "english"},
"content": {"type": "text"},
"author": {"type": "keyword"},
"created_at": {"type": "date"},
"views": {"type": "integer"}
}
}
}
es.indices.create(index='articles', body=mapping)
# Index document
doc = {
"title": "Elasticsearch Guide",
"content": "Complete guide to Elasticsearch",
"author": "John Doe",
"created_at": "2024-01-01",
"views": 100
}
es.index(index='articles', id=1, body=doc)
# Bulk indexing
from elasticsearch.helpers import bulk
actions = [
{"_index": "articles", "_id": i, "_source": doc}
for i, doc in enumerate(documents)
]
bulk(es, actions)
Search Queries
# Full-text search
query = {
"query": {
"match": {
"content": "elasticsearch guide"
}
}
}
results = es.search(index='articles', body=query)
# Boolean query
bool_query = {
"query": {
"bool": {
"must": [
{"match": {"content": "elasticsearch"}}
],
"filter": [
{"range": {"views": {"gte": 100}}}
],
"should": [
{"term": {"author": "john-doe"}}
],
"must_not": [
{"term": {"status": "draft"}}
]
}
}
}
# Multi-match query
multi_match = {
"query": {
"multi_match": {
"query": "elasticsearch guide",
"fields": ["title^2", "content"], # Boost title
"type": "best_fields"
}
}
}
# Fuzzy search
fuzzy = {
"query": {
"fuzzy": {
"title": {
"value": "elasticseerch",
"fuzziness": "AUTO"
}
}
}
}
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.
- 7d ago Changed · +2 lines · +22 tokens per session 56b87100b40f
- 12d ago First seen · 187 lines · 19 tokens per session scan A 9944ac05a6a7
elasticsearch-expert is a skill published in the GitHub repository personamanagmentlayer/pcl (40 stars, last pushed 2d ago), licensed Apache-2.0. It adds 41 tokens to every session and 968 once invoked, about $0.0002 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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