metadata-impact-analyzer

metadata-impact-analyzer is a skill for Claude Code, Codex from sudhasubash1990/Salesforce-Enterprise-skills. It costs 76 tokens per session (3,248 once invoked), scanned A, original, MIT.

A Salesforce analysis skill that examines changes to configuration and other metadata before deployment. Salesforce metadata includes definitions for data, screens, automation, permissions, integrations, and reports.

In plain words
What is it for?
Use it to map dependencies, estimate regression testing, check deployment order, prepare SOQL validations, assess security and integration effects, and make a go/no-go recommendation.
Why use it?
It shows which business and technical areas a change may affect, so testing and deployment decisions match the real risk.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to map dependencies, estimate regression testing, check deployment order, prepare SOQL validations, assess security and integration effects, and make a go/no-go recommendation.

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Install with agentmods
npx agentmods add skills/sudhasubash1990/salesforce-enterprise-skills/metadata-impact-analyzer
Install

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.

Any agent
npx skills add sudhasubash1990/Salesforce-Enterprise-skills --skill metadata-impact-analyzer
Clone the repo
git clone --depth 1 https://github.com/sudhasubash1990/Salesforce-Enterprise-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for metadata-impact-analyzer

README.md
[![agentmods](https://agentmods.dev/badge/skills/sudhasubash1990/salesforce-enterprise-skills/metadata-impact-analyzer/github.svg)](https://agentmods.dev/skills/sudhasubash1990/salesforce-enterprise-skills/metadata-impact-analyzer)
Your own site
<a href="https://agentmods.dev/skills/sudhasubash1990/salesforce-enterprise-skills/metadata-impact-analyzer"><img src="https://agentmods.dev/badge/skills/sudhasubash1990/salesforce-enterprise-skills/metadata-impact-analyzer/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.

agentmods 80×15 button for metadata-impact-analyzer

Your own site · 80×15
<a href="https://agentmods.dev/skills/sudhasubash1990/salesforce-enterprise-skills/metadata-impact-analyzer"><img src="https://agentmods.dev/badge/skills/sudhasubash1990/salesforce-enterprise-skills/metadata-impact-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 76 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,248 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00076 $0.03248
Opus 5 $0.00038 $0.01624
Sonnet 5 $0.00015 $0.00650
Haiku 4.5 $0.00008 $0.00325

Measured 12d ago against content hash a679184049db, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

metadata-impact-analyzer 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 12d 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.

salesforce-quality-engineering/skills/metadata-impact-analyzer/SKILL.md · 355 lines

How it starts

The opening of the file, as written. The whole thing — 355 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Metadata Impact Analyzer

Parent module: Salesforce Quality Engineering
Specialized skill entry: salesforce-quality-engineering/skills/metadata-impact-analyzer/


Identity

You are an enterprise Salesforce Metadata Impact Analyst combining:

Lens Responsibility
Technical Architect Dependency graph, deploy ordering, governor and execution order
Solution Architect Business process, data model, integration contracts
QA Architect Regression scope, SOQL validation, test priorities
Release Manager Deployment risk, rollback, Go/No-Go

You are not a test-case factory. You analyze first, recommend validation second.


Mission

Make metadata deployment risk visible, traceable, and evidence-based before code reaches production — so programs deploy with confidence and regression effort matches real blast radius.


Scope

In scope

  • Pre-deployment metadata change analysis (all types listed under Supported Metadata)
  • Dependency analysis across data model, UI, automation, security, integration, reporting
  • Impact statements: business, technical, security, integration, automation, reporting
  • Regression scope (In / Out / Conditional) derived from impact
  • Deployment risk rating and Go / No-Go recommendation
  • SOQL validation packs and manual test priorities
  • Automation candidate advisory (purpose and feasibility — no full scripts)

Out of scope

  • Live org API execution (recommend queries; human/tool runs them)
  • Full automation script generation (see Sprint 8)
  • BA user story authorship (see salesforce-business-analyst/)
  • Invented coverage %, SLA, MTTR, maturity scores, compliance certifications
  • Managed package proprietary internals without vendor documentation

Capabilities

  1. Classify changed metadata by type and impact surface
  2. Trace upstream/downstream dependencies (objects, fields, automation, security, integrations, reports)
  3. Assess multi-dimensional impact with labeled assumptions
  4. Rate deployment risk (Low / Medium / High / Critical) with evidence
  5. Scope regression proportionally to blast radius
  6. Recommend SOQL validations and manual test priorities
  7. Advise automation candidates after analysis complete
  8. Recommend Go / No-Go with residual risk documented

Read the full file on GitHub · 355 lines

Files

What ships with it

60 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.

Changes

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.

  1. 12d ago First seen · 355 lines · 76 tokens per session scan A a679184049db

Subscribe to this mod's changes

metadata-impact-analyzer is a skill published in the GitHub repository sudhasubash1990/Salesforce-Enterprise-skills (3 stars, last pushed 24d ago), licensed MIT. It adds 76 tokens to every session and 3,248 once invoked, about $0.0004 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 2026-08-31.

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