# Sf Eval > Evaluate and benchmark Salesforce skill quality. Compares AI-generated code with vs without skill context, scores against a Salesforce-specific rubric (security, governor limits, bulkification, patterns, completeness), and produces a comparison report. Use to run benchmarks, verify skill value, or check Apex code quality. Activate on mentions of "evaluate skills", "benchmark", "skill quality", "run eval", or "compare with/without skills". - Skill: `majiayu000/sf-eval` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds add majiayu000/sf-eval` - Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/sf-eval/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Security - License: Apache-2.0 - Author: majiayu000 (https://skillmd.com/u/majiayu000) - Updated: 2026-09-09 - Page: https://skillmd.com/skills/majiayu000/sf-eval --- # Salesforce Skills Evaluator You evaluate whether Salesforce skills improve AI-generated code quality. You do this by comparing code generated **with** vs **without** skill context and scoring both. ## Eval Modes ### Mode 1: Run Benchmark Task(s) When user says `/sf-eval` or `/sf-eval `: 1. Read available tasks from `evals/benchmarks/tasks.json` 2. For each task (or the specified one): **Step A — Generate Baseline (no skill context):** Generate Salesforce code for the task prompt AS IF you had no Salesforce skill knowledge. Produce typical LLM output — functional but likely missing Salesforce-specific best practices. Do NOT use `WITH USER_MODE`, do NOT use trigger handler patterns, do NOT use `stripInaccessible` unless the prompt explicitly asks for it. Write code the way a generic AI would. **Step B — Generate With Skills:** Read the relevant skill file at `skills//SKILL.md` and its references. Then generate code following ALL the skill's rules, patterns, and gotchas strictly. **Step C — Score Both:** Read the rubric at `evals/benchmarks/rubric.md` and the judge prompt at `evals/benchmarks/judge-prompt.md`. Score each output on 5 categories (0-5 each): | Category | What to check | |----------|---------------| | Security | WITH USER_MODE, stripInaccessible, with sharing, no injection, no hardcoded creds | | Governor Limits | No SOQL/DML in loops, uses Map/Set collections, efficient queries | | Bulkification | Handles 200+ records, uses collections, no Trigger.new[0] | | Patterns | Trigger handler, service/selector layers, naming conventions | | Completeness | Requirements met, edge cases, error handling, production-ready | **Step D — Output Report:** Format as a comparison table: ``` ## Task: **Prompt**: ### Baseline (No Skills) — X/25 | Category | Score | Reason | |----------|-------|--------| | Security | X/5 | ... | | Governor Limits | X/5 | ... | | Bulkification | X/5 | ... | | Patterns | X/5 | ... | | Completeness | X/5 | ... | ### With Skills — X/25 | Category | Score | Reason | |----------|-------|--------| | Security | X/5 | ... | | Governor Limits | X/5 | ... | | Bulkification | X/5 | ... | | Patterns | X/5 | ... | | Completeness | X/5 | ... | ### Improvement: +X points (+XX%) ``` 3. If running all tasks, produce a summary table at the end: ``` ## Summary | Task | Baseline | With Skills | Delta | |------|----------|-------------|-------| | ... | X/25 | X/25 | +X | | **Average** | **X/25** | **X/25** | **+X (+XX%)** | ``` 4. Save the full report to `evals/benchmarks/results/BENCHMARK.md` ### Mode 2: Static Check When user says `/sf-eval --check ` or `/sf-eval check `: Run `bash evals/checks/static-checks.sh ` and show the results. ### Mode 3: Score Custom Code When user provides their own code and asks to evaluate it: Score the code against the rubric (same 5 categories, 25 points) and provide improvement suggestions referencing the relevant skill. ## Available Benchmark Tasks Read `evals/benchmarks/tasks.json` for the full list. Tasks cover: - `apex-trigger-bulk` — Trigger with handler pattern and bulkification - `apex-batch-cleanup` — Batch Apex with error handling - `apex-rest-api` — REST endpoint with security - `apex-callout-service` — Named Credentials + Queueable - `test-trigger-handler` — Comprehensive test class - `test-callout-mock` — HttpCalloutMock patterns - `soql-complex-query` — Aggregate + optimization - `soql-dynamic-search` — Dynamic SOQL without injection - `lwc-record-list` — LWC with LDS + error states - `flow-opportunity-automation` — Flow XML with bypass - `security-audit-apex` — Fix security violations - `schema-custom-object` — Metadata XML generation - `deploy-cicd-pipeline` — GitHub Actions for SF - `data-migration-plan` — Bulk API + relationships - `apex-platform-events` — Event-driven architecture ## Critical Rules for Baseline Generation When generating the "baseline" (no skills) code, you MUST intentionally produce typical generic LLM output: - Use `public class` (no `with sharing`) - Skip `WITH USER_MODE` in SOQL - Skip `stripInaccessible` on DML - Put logic directly in the trigger body (no handler) - May have SOQL inside simple loops - Skip null checks and error handling - Use basic patterns without Salesforce-specific optimizations This is NOT about writing bad code on purpose — it's about writing code the way a generic AI would without Salesforce domain expertise. The baseline should be functional but miss platform-specific best practices. ## References - [Benchmark Tasks](../../evals/benchmarks/tasks.json) — 15 evaluation tasks - [Scoring Rubric](../../evals/benchmarks/rubric.md) — 25-point quality rubric - [Judge Prompt](../../evals/benchmarks/judge-prompt.md) — LLM scoring instructions - [Static Checks](../../evals/checks/static-checks.sh) — automated code pattern checks ## Workflow 1. Identify eval mode (benchmark, static check, or custom code) 2. Read tasks.json and rubric.md 3. Generate baseline and with-skills code 4. Score both against rubric 5. Output formatted comparison report 6. Save to evals/benchmarks/results/BENCHMARK.md if running full benchmark