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 deployment-risk-assessmentgit 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/deployment-risk-assessment)<a href="https://agentmods.dev/skills/banibratachatterjee/awesomesalesforceskills/deployment-risk-assessment"><img src="https://agentmods.dev/badge/skills/banibratachatterjee/awesomesalesforceskills/deployment-risk-assessment/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/deployment-risk-assessment"><img src="https://agentmods.dev/badge/skills/banibratachatterjee/awesomesalesforceskills/deployment-risk-assessment.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 | $0.00123 | $0.03007 |
| Opus 5.5 | $0.00049 | $0.01203 |
| Sonnet 5.5 | $0.00025 | $0.00601 |
| Haiku 4.5 | $0.00012 | $0.00301 |
Grade A, and why
deployment-risk-assessment 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 — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deployment Risk Assessment
Use this skill to classify deployment risk by component before a release window opens, define rollback trigger conditions in writing, and assign decision authority so that rollback calls are made on pre-agreed criteria rather than improvised under pressure.
Before Starting
Gather this context before working on anything in this domain:
- Release scope: What metadata types are included? Permissions, flows, integrations, and sharing rules carry higher inherent risk than layout and list view changes.
- Deployment method: Unlocked packages support version-based rollback by redeploying the previous version. Change Sets and CLI-based org deploys have no native undo — rollback requires a pre-retrieve backup or a manually authored destructive change.
- Validation evidence: Which sandboxes ran a full deployment validation, and did they match the production metadata state at validation time?
- Business window: When does the deployment open, how long is the window, and what is the tolerance for staying in a broken state?
- Decision authority: Who has go/no-go authority, who can call rollback, and how are they reachable during off-hours releases?
Core Concepts
The Three Failure Domains
The Salesforce Well-Architected framework frames deployment risk across three failure domains:
- People — Missing decision authority, unclear escalation paths, or a team unfamiliar with the rollback procedure under time pressure.
- Process — No documented rollback trigger conditions, skipping lower-environment validation, or merging unrelated changes into a single release with no decomposition.
- Technology — Metadata dependencies not resolved before deployment, missing pre-retrieve backup, or relying on the Salesforce UI for a rollback mechanism that does not exist.
Risk classification must address all three domains. A release that looks technically simple can be high-risk on the people dimension if the release manager is unavailable and no alternate decision-maker is named.
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.
- 1mo ago First seen · 223 lines · 123 tokens per session scan A e3888e6b6e70
deployment-risk-assessment is a skill published in the GitHub repository BanibrataChatterjee/AwesomeSalesforceSkills (4 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 123 tokens to every session and 3,007 once invoked, about $0.0005 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 2026-09-03.
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