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 BanibrataChatterjee/AwesomeSalesforceSkills --skill data-cloud-identity-resolutiongit clone --depth 1 https://github.com/BanibrataChatterjee/AwesomeSalesforceSkillsWrote 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/banibratachatterjee/awesomesalesforceskills/data-cloud-identity-resolution)<a href="https://agentmods.dev/skills/banibratachatterjee/awesomesalesforceskills/data-cloud-identity-resolution"><img src="https://agentmods.dev/badge/skills/banibratachatterjee/awesomesalesforceskills/data-cloud-identity-resolution/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/banibratachatterjee/awesomesalesforceskills/data-cloud-identity-resolution"><img src="https://agentmods.dev/badge/skills/banibratachatterjee/awesomesalesforceskills/data-cloud-identity-resolution.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 | $0.00096 | $0.04539 |
| Opus 5 | $0.00048 | $0.02269 |
| Sonnet 5 | $0.00019 | $0.00908 |
| Haiku 4.5 | $0.00010 | $0.00454 |
Grade A, and why
data-cloud-identity-resolution 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 9d 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 — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Cloud Identity Resolution
This skill activates when a practitioner needs to configure, modify, or diagnose identity resolution rulesets in Data Cloud — the platform capability that merges records from different data sources into a single Unified Individual profile using match rules and reconciliation rules. It covers ruleset design, match rule type selection, reconciliation rule behavior, cross-device identity, and the hard org limits that make these configurations difficult to reverse.
Before Starting
Gather this context before working on anything in this domain:
- How many identity resolution rulesets already exist in the org? Navigate to Data Cloud Setup > Identity Resolution. The hard platform limit is 2 rulesets per org, counting any auto-created ruleset from the Starter Data Bundle. This limit cannot be raised with a support case — it is a hard constraint.
- Have all required DMOs been mapped? Identity resolution requires source records to be mapped to the Individual DMO (for person identity) and at least one Contact Point DMO (Email, Phone, or Address) before match rules can reference those fields. Run the Data Cloud health check or inspect the data stream mappings.
- Is the ruleset ID known? Every ruleset is assigned a 4-character ID at creation time. This ID cannot be changed after the ruleset is created. It is embedded in downstream references, including activation targets and segmentation filters.
- What is the recency and completeness of source data? Reconciliation rules use field-level recency (most-recently-updated record wins) or priority-based source precedence. If source data has irregular update timestamps, the reconciliation output may not reflect the most trusted value.
- Is real-time resolution required? Only Exact and Exact Normalized match methods are evaluated in real-time processing. Fuzzy matching (first name only) is batch-only. This distinction affects resolution latency SLAs.
Core Concepts
What ships with it
6 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.
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.
- 9d ago First seen · 234 lines · 96 tokens per session scan A f63c28a29fb5
data-cloud-identity-resolution is a skill published in the GitHub repository BanibrataChatterjee/AwesomeSalesforceSkills (3 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 96 tokens to every session and 4,539 once invoked, about $0.0005 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 2026-09-03.
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