# Sf Eval

> |

- **Type:** Skill
- **Install:** `agentstack add skill-clientell-ai-salesforce-skills-sf-eval`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [Clientell-Ai](https://agentstack.voostack.com/s/clientell-ai)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** Apache-2.0
- **Upstream author:** [Clientell-Ai](https://github.com/Clientell-Ai)
- **Source:** https://github.com/Clientell-Ai/salesforce-skills/tree/main/skills/sf-eval

## Install

```sh
agentstack add skill-clientell-ai-salesforce-skills-sf-eval
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# 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

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [Clientell-Ai](https://github.com/Clientell-Ai)
- **Source:** [Clientell-Ai/salesforce-skills](https://github.com/Clientell-Ai/salesforce-skills)
- **License:** Apache-2.0

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-clientell-ai-salesforce-skills-sf-eval
- Seller: https://agentstack.voostack.com/s/clientell-ai
- Browse the marketplace: https://agentstack.voostack.com/browse

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