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 Clientell-Ai/salesforce-skills --skill sf-datagit clone --depth 1 https://github.com/Clientell-Ai/salesforce-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/clientell-ai/salesforce-skills/sf-data)<a href="https://agentmods.dev/skills/clientell-ai/salesforce-skills/sf-data"><img src="https://agentmods.dev/badge/skills/clientell-ai/salesforce-skills/sf-data/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/clientell-ai/salesforce-skills/sf-data"><img src="https://agentmods.dev/badge/skills/clientell-ai/salesforce-skills/sf-data.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00087 | $0.01637 |
| Opus 5.5 | $0.00035 | $0.00655 |
| Sonnet 5.5 | $0.00017 | $0.00327 |
| Haiku 4.5 | $0.00009 | $0.00164 |
Grade A, and why
sf-data 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 1mo 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 — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Migration & Management
You are a Salesforce data specialist. Handle data operations safely and efficiently.
Data Operations
Query and Export
# Query records
sf data query -q "SELECT Id, Name, Industry FROM Account WHERE Industry != null LIMIT 100" --target-org myOrg
# Export to CSV
sf data query -q "SELECT Id, Name, Industry FROM Account" --target-org myOrg --result-format csv > accounts.csv
# Export to JSON
sf data query -q "SELECT Id, Name FROM Account" --target-org myOrg --result-format json > accounts.json
# Bulk query (large datasets)
sf data query -q "SELECT Id, Name FROM Account" --target-org myOrg --bulk
Import and Upsert
# Insert records from CSV
sf data import tree -f data/accounts.json --target-org myOrg
# Bulk upsert
sf data upsert bulk -s Account -f accounts.csv -i External_Id__c --target-org myOrg
# Insert with plan (preserves relationships)
sf data import tree -p data/plan.json --target-org myOrg
Data Plan for Related Records
[
{
"sobject": "Account",
"saveRefs": true,
"resolveRefs": false,
"files": ["Account.json"]
},
{
"sobject": "Contact",
"saveRefs": false,
"resolveRefs": true,
"files": ["Contact.json"]
}
]
Sandbox Seeding Script
#!/bin/bash
# seed-sandbox.sh — Create test data in a sandbox
ORG_ALIAS="${1:-sandbox}"
echo "Seeding data in $ORG_ALIAS..."
# Insert accounts
sf data import tree -f data/seed/accounts.json --target-org "$ORG_ALIAS"
# Insert contacts (references accounts)
sf data import tree -f data/seed/contacts.json --target-org "$ORG_ALIAS"
# Insert opportunities
sf data import tree -f data/seed/opportunities.json --target-org "$ORG_ALIAS"
echo "Seeding complete."
Anonymous Apex for Data Setup
# Run anonymous Apex for complex data setup
sf apex run -f scripts/seed-data.apex --target-org myOrg
// scripts/seed-data.apex
List<Account> accounts = new List<Account>();
for (Integer i = 0; i < 100; i++) {
accounts.add(new Account(
Name = 'Test Account ' + i,
Industry = 'Technology',
BillingState = 'CA'
));
}
insert accounts;
System.debug('Inserted ' + accounts.size() + ' accounts');
What ships with it
1 file 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.
- 1mo ago First seen · 196 lines · 87 tokens per session scan A 4cf803af0de0
sf-data is a skill published in the GitHub repository Clientell-Ai/salesforce-skills (20 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 87 tokens to every session and 1,637 once invoked, about $0.0003 per session on Opus 5.5. 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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