Searching Media

Name: Searching Media
Author: forcedotcom

forcedotcom/sf-skills

2.1k installs
763 repo stars
Updated July 24, 2026
forcedotcom/sf-skills

data360-query runs Data Cloud SQL, async queries, vector or hybrid search, and metadata describe via sf data360 CLI.

About

The data360-query skill covers Salesforce Data Cloud retrieve-phase work: sync SQL, paginated sqlv2, async query workflows, table describe, vector search, hybrid search, and search-index operations. Use when tasks involve sf data360 query, search-index, metadata, profile, or insight inspection. Delegate standard CRM SOQL to platform-soql-query, segment design to data360-segment, and STDM tracing to agentforce-observe. Gather org alias, result-set size needs, and table or index names first. Run diagnose-org with phase retrieve before relying on query surfaces. Prefer describe before guessing columns, sqlv2 or async for larger sets, and vector or hybrid only when index lifecycle is healthy. Examples include COUNT on ssot__Individual__dlm, describe table, vector and hybrid queries against Knowledge_Index with optional prefilter. Gotchas: Data Cloud SQL is not SOQL, double-quote table names, HNSW userValues often empty on create, and query describe needs a known DMO after readiness passes. Output reports retrieve task type, org, object, commands, verification, and next step.

Owns sf data360 query, search-index, metadata, profile, and insight retrieve tasks.
Run diagnose-org --phase retrieve before query or search-index work.
sqlv2 and async-create for medium and large result sets; describe before guessing fields.
Vector and hybrid search require healthy search-index lifecycle and real index names.
Not SOQL: double-quote DMO table names; delegate CRM SOQL to platform-soql-query.

Searching Media by the numbers

2,131 all-time installs (skills.sh)
+7 installs in the week ending Jul 28, 2026 (Skillselion tracking)
Ranked #46 of 2,066 Data Science & ML skills by installs in the Skillselion catalog
Security screen: HIGH risk (skills.sh audit)
Data as of Jul 28, 2026 (Skillselion catalog sync)

At a glance

searching-media capabilities & compatibility

Capabilities: retrieve phase org readiness classification · sync, sqlv2, and async sql execution · table describe and field discovery · vector and hybrid search with prefilter · search index list and curated json examples
Use cases: database · data analysis · research

From the docs

What searching-media says it does

Treat Data Cloud SQL as its own query language, not SOQL.

SKILL.md

Use vector search or hybrid search only when the search index lifecycle is healthy.

SKILL.md

npx skills add https://github.com/forcedotcom/sf-skills --skill searching-media

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Installs	2.1k
repo stars	★ 763
Security audit	2 / 3 scanners passed
Last updated	July 24, 2026
Repository	forcedotcom/sf-skills ↗

How do I query, describe, or search Salesforce Data Cloud objects with the community sf data360 plugin?

Run Salesforce Data Cloud SQL, async queries, vector or hybrid search, and metadata describe via sf data360 CLI with readiness checks.

Who is it for?

Data Cloud-enabled orgs needing SQL counts, exports, schema describe, or semantic vector or hybrid search.

Skip if: Skip for plain CRM SOQL, segment or calculated insight design, or STDM parquet session tracing.

When should I use this skill?

User runs Data Cloud SQL, async queries, vector search, search-index workflows, or metadata introspection.

What you get

Verified retrieve output with task type, org, object, commands run, row or schema proof, and suggested next step.

Retrieved media asset references
Routed CMS search results

Files

SKILL.mdMarkdownGitHub ↗

data360-query: Data Cloud Retrieve Phase

Use this skill when the user needs query, search, and metadata introspection for Data Cloud: sync SQL, paginated SQL, async query workflows, table describe, vector search, hybrid search, or search index operations.

When This Skill Owns the Task

Use data360-query when the work involves:

sf data360 query *
sf data360 search-index *
sf data360 metadata *
sf data360 profile * or sf data360 insight * inspection
understanding Data Cloud SQL results or query shape

Delegate elsewhere when the user is:

writing standard CRM SOQL only → platform-soql-query
designing segment or calculated insight assets → data360-segment
analyzing STDM/session tracing/parquet telemetry → agentforce-observe

---

Required Context to Gather First

Ask for or infer:

target org alias
whether the user needs quick count, medium result set, large export, schema inspection, or semantic search
table/index name if known
whether the task is read-only SQL or search-index lifecycle management

---

Core Operating Rules

Treat Data Cloud SQL as its own query language, not SOQL.
Run the shared readiness classifier before relying on query/search surfaces: node ../data360-orchestrate/scripts/diagnose-org.mjs -o <org> --phase retrieve --json.
Use describe before guessing columns.
Prefer sqlv2 or async query flows for larger result sets.
Use vector search or hybrid search only when the search index lifecycle is healthy.
Keep STDM/parquet/session-tracing workflows out of this skill family.

---

Recommended Workflow

1. Classify readiness for retrieve work

node ../data360-orchestrate/scripts/diagnose-org.mjs -o <org> --phase retrieve --json
# optional query-plane probe, only with a real table name
node ../data360-orchestrate/scripts/diagnose-org.mjs -o <org> --phase retrieve --describe-table MyDMO__dlm --json

2. Choose the smallest correct query shape

sf data360 query sql -o <org> --sql 'SELECT COUNT(*) FROM "ssot__Individual__dlm"' 2>/dev/null
sf data360 query sqlv2 -o <org> --sql 'SELECT * FROM "ssot__Individual__dlm"' 2>/dev/null
sf data360 query async-create -o <org> --sql 'SELECT * FROM "ssot__Individual__dlm"' 2>/dev/null

3. Use describe before guessing fields

sf data360 query describe -o <org> --table ssot__Individual__dlm 2>/dev/null

4. Use vector or hybrid search only when an index exists

sf data360 search-index list -o <org> 2>/dev/null
sf data360 query vector -o <org> --index Knowledge_Index --query "reset password" --limit 5 2>/dev/null
sf data360 query hybrid -o <org> --index Knowledge_Index --query "reset password" --limit 5 2>/dev/null
sf data360 query hybrid -o <org> --index Insurance_Index --query "weather damage coverage" --prefilter "Type_of_Insurance__c='Home'" --limit 10 2>/dev/null

5. Reuse curated search-index examples when creating indexes

Use the phase-owned examples instead of inventing JSON from scratch:

examples/search-indexes/vector-knowledge.json
examples/search-indexes/hybrid-structured.json

---

High-Signal Gotchas

Data Cloud SQL is not SOQL.
Table names should be double-quoted in SQL.
sqlv2 is better than ad hoc OFFSET paging for medium result sets.
async query is preferable for large results.
search-index operations and vector/hybrid queries depend on the index lifecycle being healthy.
Hybrid search can use --prefilter, but only on fields configured as prefilter-capable when the search index was created.
HNSW index parameters are typically read-only on create; leave userValues: [] unless the platform explicitly documents otherwise.
query describe is not a universal tenant probe; only run it with a known DMO or DLO table after broader readiness has been confirmed.

---

Output Format

Retrieve task: <sql / sqlv2 / async / describe / vector / search-index>
Target org: <alias>
Target object: <table or index>
Commands: <key commands run>
Verification: <query rows / schema / status>
Next step: <segment / harmonize / follow-up>

---

References

README.md
examples/search-indexes/vector-knowledge.json
examples/search-indexes/hybrid-structured.json
../data360-orchestrate/assets/definitions/search-index.template.json
../data360-orchestrate/references/plugin-setup.md
../data360-orchestrate/references/feature-readiness.md

{
  "label": "<INDEX_NAME>",
  "developerName": "<INDEX_NAME>",
  "description": "Hybrid search index on a structured Data Cloud DMO",
  "sourceDmoDeveloperName": "<SOURCE_DMO>__dlm",
  "chunkDmoName": "<INDEX_NAME> chunk",
  "chunkDmoDeveloperName": "<INDEX_NAME>_chunk",
  "vectorDmoName": "<INDEX_NAME> index",
  "vectorDmoDeveloperName": "<INDEX_NAME>_index",
  "searchType": "HYBRID",
  "vectorEmbedding": {
    "vectorEmbeddingRelatedFields": []
  },
  "rankingConfigurations": [],
  "chunkingConfiguration": {
    "fieldLevelConfigurations": [
      {
        "sourceDmoDeveloperName": "<SOURCE_DMO>__dlm",
        "sourceDmoFieldDeveloperName": "<TEXT_FIELD>__c",
        "config": {
          "id": "passage_extraction",
          "userValues": [
            { "id": "max_tokens", "value": "512" },
            { "id": "strip_html", "value": "true" }
          ]
        }
      }
    ]
  },
  "vectorEmbeddingConfiguration": {
    "embeddingModel": {
      "id": "e5_large_v2",
      "userValues": [
        { "id": "dimension", "value": "1024" },
        { "id": "max_token_limit", "value": "512" }
      ]
    },
    "index": {
      "id": "HNSW",
      "userValues": []
    },
    "similarityMetric": "COSINE"
  }
}

{
  "label": "My_kav",
  "developerName": "My_kav",
  "sourceDmoDeveloperName": "ssot__KnowledgeArticleVersion__dlm",
  "chunkDmoName": "My_kav chunk",
  "chunkDmoDeveloperName": "My_kav_chunk",
  "vectorDmoName": "My_kav index",
  "vectorDmoDeveloperName": "My_kav_index",
  "searchType": "VECTOR",
  "vectorEmbedding": {
    "vectorEmbeddingRelatedFields": []
  },
  "chunkingConfiguration": {
    "fieldLevelConfigurations": [
      {
        "sourceDmoDeveloperName": "ssot__KnowledgeArticleVersion__dlm",
        "sourceDmoFieldDeveloperName": "ssot__Name__c",
        "config": {
          "id": "passage_extraction",
          "userValues": [
            { "id": "strip_html", "value": "true" },
            { "id": "max_tokens", "value": "512" }
          ]
        }
      }
    ]
  },
  "vectorEmbeddingConfiguration": {
    "embeddingModel": {
      "id": "e5_large_v2",
      "userValues": [
        { "id": "dimension", "value": "1024" },
        { "id": "max_token_limit", "value": "512" }
      ]
    },
    "index": {
      "id": "HNSW",
      "userValues": []
    },
    "similarityMetric": "COSINE"
  },
  "rankingConfigurations": []
}

data360-query

Query and search workflows for Salesforce Data Cloud.

Use this skill for

quick SQL counts
paginated SQL (sqlv2)
async query lifecycles
table describe
vector search
hybrid search with optional prefilter
search index inspection and lifecycle work

Example requests

"Run a Data Cloud SQL query against unified profiles"
"Describe this Data Cloud table before I write SQL"
"Help me troubleshoot vector search in Data Cloud"
"Run a hybrid search with a prefilter in Data Cloud"
"Create and inspect a search index"

Common commands

sf data360 query sql -o myorg --sql 'SELECT COUNT(*) FROM "ssot__Individual__dlm"' 2>/dev/null
sf data360 query describe -o myorg --table ssot__Individual__dlm 2>/dev/null
sf data360 search-index list -o myorg 2>/dev/null
sf data360 query vector -o myorg --index Knowledge_Index --query "reset password" --limit 5 2>/dev/null
sf data360 query hybrid -o myorg --index Knowledge_Index --query "reset password" --limit 5 2>/dev/null

Example payloads

examples/search-indexes/vector-knowledge.json
examples/search-indexes/hybrid-structured.json

References

SKILL.md
../data360-orchestrate/assets/definitions/search-index.template.json
CREDITS.md

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Forks & variants (1)

Searching Media has 1 known copy in the catalog totaling 1.5k installs. They canonicalize to this original listing.

forcedotcom - 1.5k installs

How it compares

Activate searching-media as the single media gateway in Salesforce agent stacks instead of invoking CMS search tools ad hoc.

FAQ

Is Data Cloud SQL the same as SOQL?

No. Treat Data Cloud SQL as its own language with double-quoted table names; use platform-soql-query for CRM SOQL.

When should I use async query instead of sql?

Prefer sqlv2 for medium sets and async-create for large exports after readiness diagnose passes.

What before vector or hybrid search?

Confirm search-index list health and use real index names; hybrid prefilter only on configured prefilter fields.

Is Searching Media safe to install?

skills.sh reports 2 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

Data Science & MLdatabasesanalytics

About

Searching Media by the numbers

searching-media capabilities & compatibility

What searching-media says it does

Add your badge

How do I query, describe, or search Salesforce Data Cloud objects with the community sf data360 plugin?

Who is it for?

When should I use this skill?

What you get

Files

data360-query: Data Cloud Retrieve Phase

When This Skill Owns the Task

Required Context to Gather First

Core Operating Rules

Recommended Workflow

1. Classify readiness for retrieve work

2. Choose the smallest correct query shape

3. Use describe before guessing fields

4. Use vector or hybrid search only when an index exists

5. Reuse curated search-index examples when creating indexes

High-Signal Gotchas

Output Format

References

Credits & Acknowledgments

data360-query

Use this skill for

Example requests

Common commands

Example payloads

References

Related skills

Forks & variants (1)

How it compares

FAQ

Is Data Cloud SQL the same as SOQL?

When should I use async query instead of sql?

What before vector or hybrid search?

Is Searching Media safe to install?

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