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 Jaganpro/sf-skills --skill sf-datacloud-connectgit clone --depth 1 https://github.com/Jaganpro/sf-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/jaganpro/sf-skills/sf-datacloud-connect)<a href="https://agentmods.dev/skills/jaganpro/sf-skills/sf-datacloud-connect"><img src="https://agentmods.dev/badge/skills/jaganpro/sf-skills/sf-datacloud-connect/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/jaganpro/sf-skills/sf-datacloud-connect"><img src="https://agentmods.dev/badge/skills/jaganpro/sf-skills/sf-datacloud-connect.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket warn
- Snyk 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 | $0.00116 | $0.01852 |
| Opus 5 | $0.00058 | $0.00926 |
| Sonnet 5 | $0.00023 | $0.00370 |
| Haiku 4.5 | $0.00012 | $0.00185 |
Grade A, and why
sf-datacloud-connect 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 — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
sf-datacloud-connect: Data Cloud Connect Phase
Use this skill when the user needs source connection work: connector discovery, connection metadata, connection testing, source-object browsing, connector schema inspection, or connector-specific setup payloads for external sources.
When This Skill Owns the Task
Use sf-datacloud-connect when the work involves:
sf data360 connection *- connector catalog inspection
- connection creation, update, test, or delete
- browsing source objects, fields, databases, or schemas
- identifying connector types already in use
- preparing connector definitions for Snowflake, SharePoint Unstructured, or Ingestion API sources
Delegate elsewhere when the user is:
- creating data streams or DLOs → sf-datacloud-prepare
- creating DMOs, mappings, IR rulesets, or data graphs → sf-datacloud-harmonize
- writing Data Cloud SQL or search-index workflows → sf-datacloud-retrieve
Required Context to Gather First
Ask for or infer:
- target org alias
- connector type or source system
- whether the user wants inspection only or live mutation
- connection name or ID if one already exists
- whether credentials are already configured outside the CLI
- whether the user also expects stream creation right after connection setup
- whether the source is a database, an unstructured document source, or an Ingestion API feed
Core Operating Rules
- Verify the plugin runtime first; see ../sf-datacloud/references/plugin-setup.md.
- Run the shared readiness classifier before mutating connections:
node ~/.claude/skills/sf-datacloud/scripts/diagnose-org.mjs -o <org> --phase connect --json. - Prefer read-only discovery before connection creation.
- Suppress linked-plugin warning noise with
2>/dev/nullfor standard usage. - Remember that
connection listrequires--connector-type. - For
connection test, pass--connector-typewhen resolving a non-Salesforce connection by name. - Discover existing connector types from streams first when the org is unfamiliar.
- Use curated example payloads before inventing connector-specific credentials or parameters.
- For connector types outside the curated examples, inspect a known-good UI-created connection via REST before building JSON.
- Do not promise API-based stream creation for every connector type just because connection creation succeeds.
What ships with it
9 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.
- CREDITS.md 323 B
- examples/connections/heroku-postgres.json 498 B
- examples/connections/ingest-api-connection.json 97 B
- examples/connections/ingest-api-schema.json 582 B
- examples/connections/redshift.json 536 B
- examples/connections/sharepoint-unstructured.json 469 B
- examples/connections/snowflake-connection.json 860 B
- LICENSE 1.1 KB
- README.md 2.6 KB
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 · 164 lines · 116 tokens per session scan A 3dd2bdebc929
sf-datacloud-connect is a skill published in the GitHub repository Jaganpro/sf-skills (423 stars, last pushed 4mo ago), licensed MIT. It adds 116 tokens to every session and 1,852 once invoked, about $0.0006 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.
Other skills, from other repositories
event-store-design
Design and implement event stores for event-sourced systems. Use when building event sourcing infrastructure, choosing event store technologies, or implementing event persistence patterns.
convex-explain-app
Explain an existing Convex app — data model + relationships, public vs internal functions, auth/ownership model, components, a request→data flow — read from the schema and function surface. Read-only.
platform-custom-field-generate
Use this skill when users need to create, generate, or validate Salesforce Custom Field metadata. Trigger when users mention custom fields, field types, Roll-up Summary fields, Master-Detail relationships, Lookup relationships, formula fields, picklists, dependent (controlling) picklists, referencing a value set from…
durable-objects
Build, debug, or review Cloudflare Durable Objects code for persistent state and coordination.
field-service-sobject-create-configure
Headless 360 REST API deployment step for creating sObject records. Handles describe-based field discovery, required-field derivation, entity-relationship ordering, and composite graph transactions. Use this skill when a designer skill (or a user directly) needs to create sObject records after design confirmation…
nornicdb-grpc
Drive NornicDB over gRPC — the Qdrant-compatible surface (Collections, Points, Snapshots) plus the additive NornicSearch service. Use when ingesting via Qdrant SDKs, migrating from Qdrant, or running hybrid text+vector search from a non-Bolt client. Covers connection, RPC catalog, collection→database mapping…