Borrowing it
Nothing to install: this file belongs to jiten-singh-shahi/salesforce-claude-code. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/jiten-singh-shahi/salesforce-claude-code/main/.cursor/skills/prompt-optimizer/SKILL.mdgit clone --depth 1 https://github.com/jiten-singh-shahi/salesforce-claude-codeWrote 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/jiten-singh-shahi/salesforce-claude-code/prompt-optimizer)<a href="https://agentmods.dev/skills/jiten-singh-shahi/salesforce-claude-code/prompt-optimizer"><img src="https://agentmods.dev/badge/skills/jiten-singh-shahi/salesforce-claude-code/prompt-optimizer/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/jiten-singh-shahi/salesforce-claude-code/prompt-optimizer"><img src="https://agentmods.dev/badge/skills/jiten-singh-shahi/salesforce-claude-code/prompt-optimizer.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 | $0.00040 | $0.03420 |
| Opus 5 | $0.00020 | $0.01710 |
| Sonnet 5 | $0.00008 | $0.00684 |
| Haiku 4.5 | $0.00004 | $0.00342 |
Grade A, and why
prompt-optimizer 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 — 367 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prompt Optimizer
Analyze a draft prompt, critique it, match it to SCC ecosystem components, and output a complete optimized prompt the user can paste and run.
When to Use
- User says "optimize this prompt", "improve my prompt", "rewrite this prompt"
- User says "help me write a better prompt for..."
- User says "what's the best way to ask Claude Code to..."
- User pastes a draft prompt and asks for feedback or enhancement
- User says "I don't know how to prompt for this"
- User says "how should I use SCC for..."
- User explicitly invokes
/prompt-optimizer
Do Not Use When
- User wants the task done directly (just execute it)
- User says "optimize this code", "optimize performance" — these are refactoring tasks, not prompt optimization
- User is asking about SCC configuration (use
configure-sccinstead) - User wants a skill inventory (use
/sf-harness-auditskill instead) - User says "just do it"
How It Works
Advisory only — do not execute the user's task.
Do NOT write code, create files, run commands, or take any implementation action. Your ONLY output is an analysis plus an optimized prompt.
If the user says "just do it" or "don't optimize, just execute", do not switch into implementation mode inside this skill. Tell the user this skill only produces optimized prompts, and instruct them to make a normal task request if they want execution instead.
Run this 6-phase pipeline sequentially. Present results using the Output Format below.
Analysis Pipeline
Phase 0: Project Detection
Before analyzing the prompt, detect the current project context:
- Check if a
CLAUDE.mdexists in the working directory — read it for project conventions - Detect tech stack from project files:
sfdx-project.json→ Salesforce (Apex / LWC / SOQL / Flow / Agentforce)package.json→ Node.js / LWC tooling / Jest tests
- Note detected tech stack for use in Phase 3 and Phase 4
If no project files are found (e.g., the prompt is abstract or for a new project), skip detection and flag "tech stack unknown" in Phase 4.
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 · 367 lines · 40 tokens per session scan A a2bd923b3932
prompt-optimizer is a skill published in the GitHub repository jiten-singh-shahi/salesforce-claude-code (16 stars, last pushed 2mo ago), licensed MIT. It adds 40 tokens to every session and 3,420 once invoked, about $0.0002 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.
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