Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Developer Tools
Elasticsearch
Query and index Elasticsearch with proper mappings, analyzers, and search patterns.
skill openclawclawhub Free
Query and index Elasticsearch with proper mappings, analyzers, and search patterns.
⬇ 0 downloads ★ 0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- ivangdavila
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Mapping Mistakes
Always define explicit mappings—dynamic mapping guesses wrong (first "123" makes field integer, later "abc" fails) text for full-text search, keyword for exact match/aggregations—using text for IDs breaks filters Can't change field type after indexing—must reindex to new index with correct mapping Set dynamic: "strict" to reject unmapped fields—catches typos in field names
Text vs Keyword
text is analyzed (tokenized, lowercased)—"Quick Brown" matches search for "quick" keyword is exact bytes—"Quick Brown" only matches exactly "Quick Brown" Need both? Use multi-field: "title": { "type": "text", "fields": { "raw": { "type": "keyword" }}} Sort/aggregate on title.raw, search on title
Query vs Filter Context
Query context calculates relevance score—expensive, use for search ranking Filter context is yes/no—cacheable, use for exact conditions (status, date ranges) Combine: bool.must for scoring, bool.filter for filtering without scoring Range queries on dates/numbers almost always belong in filter, not query
Analyzers
standard analyzer lowercases and removes punctuation—fine for most text keyword analyzer keeps exact string—use for codes, SKUs, emails Language analyzers (english) stem words—"running" matches "run" Test analyzer with _analyze endpoint before indexing—surprises in production hurt
Nested vs Object
Object type flattens arrays—{"tags": [{"key":"a","val":1}, {"key":"b","val":2}]} becomes tags.key: [a,b], tags.val: [1,2] Flattened loses association—query key=a AND val=2 incorrectly matches above Use nested type to preserve object boundaries—requires nested query wrapper Nested is expensive—avoid for high-cardinality arrays
Pagination Traps
from + size limited to 10,000 hits—deep pagination fails search_after for deep pagination—requires consistent sort, typically _id Scroll API for bulk export—keeps point-in-time view, but ties up resources Don't use scroll for user pagination—search_after is correct choice
Bulk Operations
Never index documents one-by-one—use _bulk API, 5-15MB batches Bulk format: newline-delimited JSON, action line then document line Check response for partial failures—bulk can succeed overall with individual doc errors Set refresh=false during bulk loads—refresh after batch completes
Performance
_source: false with stored_fields if you don't need full document—reduces I/O Use filter for cacheable conditions—Elasticsearch caches filter results Avoid leading wildcards (*term)—forces full scan; use reverse field for suffix search profile: true shows query execution breakdown—find slow clauses
Sharding
Shard size 10-50GB optimal—too small = overhead, too large = slow recovery Number of shards fixed at creation—can't reshard without reindexing Replicas for read throughput and availability—set based on query load Start with 1 shard for small indices—over-sharding kills performance
Index Management
Use index templates—new indices get consistent mappings and settings Use aliases for zero-downtime reindexing—point alias to new index after reindex ILM (Index Lifecycle Management) for time-series—auto-rollover, delete old indices Close unused indices to free memory—closed index uses no heap
Aggregations
terms agg needs keyword field—text fields fail or give garbage Default size: 10 on terms agg—increase to get all buckets, or use composite Cardinality is approximate (HyperLogLog)—exact count requires scanning all docs Nested aggs require nested wrapper—matches nested query pattern
Common Errors
"cluster_block_exception"—disk > 85%, cluster goes read-only; clear disk, reset with _cluster/settings "version conflict"—concurrent update; retry with retry_on_conflict or use optimistic locking "circuit_breaker_exception"—query uses too much memory; reduce aggregation scope Mapping explosion from dynamic fields—set index.mapping.total_fields.limit and use strict mapping
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs
- SKILL.md