sf-docs: Salesforce Documentation Retrieval & Grounding

Expert Salesforce documentation researcher focused on

official sources

. This skill exists to make documentation lookup reliable when generic web search or naive page fetching fails on Salesforce's JavaScript-heavy docs experience.

sf-docs

is a

core sf-skills capability

. It should always be installed with the skill suite.

Core Responsibilities

Official Docs Retrieval

Find authoritative answers from Salesforce documentation first

Local-First Search

Use a local qmd index when available for speed and accuracy

Salesforce-Aware Fallback

When qmd is unavailable or weak, use Salesforce-specific retrieval patterns instead of generic web fetch

Source Grounding

Return answers with exact source URLs, guide names, and retrieval notes

Cross-Skill Support

Serve as the documentation lookup layer for other

sf-*

skills

Runtime Modes

Mode A: qmd-Enabled

Use this mode when qmd is installed and a local Salesforce docs corpus exists.

Preferred flow:

Detect qmd availability

Query qmd first

Evaluate result quality

If results are strong, answer from local docs

If results are weak or missing, fall back to Salesforce-aware scraping

Mode B: No-qmd

Use this mode when qmd is not installed or no local corpus exists.

Preferred flow:

Identify the most likely Salesforce doc family

Use Salesforce-aware discovery and retrieval patterns

Prefer official URLs over summaries from third-party blogs

Fall back to official PDFs when web pages are unstable or shell-rendered

Return grounded findings with source links and any uncertainty called out

Claude Code operator shortcut:

When the local

sf-docs

helper scripts are installed, prefer the built-in retrieval command over ad-hoc search-engine probing:

python3 ~/.claude/skills/sf-docs/scripts/cli.py retrieve

\

--query

""

\

--mode

no_qmd

For hard

help.salesforce.com

questions, this command applies the local no-qmd retrieval flow, including targeted Help article discovery and browser-based rendering.

Runtime Detection

sf-docs

should detect qmd

at runtime

, not just rely on installer choices.

Use this detection order:

Check whether the

qmd

CLI is available on

PATH

Check whether a local Salesforce docs corpus exists

If qmd exists but the local corpus/index is missing or effectively empty, treat the request as

no-qmd mode

If qmd exists and the corpus is populated, use

qmd-enabled mode

Reference:

references/local-corpus-layout.md

Fallback Triggers

Treat qmd results as

weak

and fall back when any of the following happen:

No results returned

Results are clearly from the wrong Salesforce product or guide family

Results lack the exact concept, API name, CLI command, or error term requested

Results are too fragmentary to answer confidently

Results appear stale and the query is obviously release-sensitive

Rule

Prefer a reliable Salesforce-specific fallback over confidently answering from a poor local hit.

Salesforce Documentation Retrieval Playbook

1. Identify the Doc Family First

Classify the request before searching:

Family

Typical Sources

Use For

Developer Docs

developer.salesforce.com/docs/...

Apex, APIs, LWC, metadata, Agentforce developer docs

Salesforce Help

help.salesforce.com/...

Setup UI steps, admin guides, feature configuration

Platform Guides

developer.salesforce.com/docs/platform/...

Newer guide-style docs with cleaner URLs

Atlas / Legacy Guides

developer.salesforce.com/docs/atlas.en-us.*

Older but still official guide and reference material

Official PDFs

resources.docs.salesforce.com/...pdf/...

Large guide bundles, stable offline extraction

2. Prefer Exact Guide Paths Over Homepage Search

Avoid stopping at broad pages like the docs homepage unless you are discovering guide roots.

Instead, resolve toward:

A specific guide root

A specific article or page

A guide PDF when page-level retrieval is unstable

3. Retrieval Patterns for

developer.salesforce.com

Use these patterns deliberately:

Modern platform guide

:

developer.salesforce.com/docs/platform/...

Legacy Atlas guide

:

developer.salesforce.com/docs/atlas.en-us..meta/...

Guide PDF candidate

derive

and try the matching official PDF URL

When an HTML page fails because of JavaScript rendering, shell content, or soft errors, try:

the guide root

the legacy Atlas variant if known

the official PDF

4. Retrieval Patterns for

help.salesforce.com

Help pages often fail with generic web fetch because of client-side rendering and site chrome.

Use this approach:

Prefer exact

help.salesforce.com/s/articleView?id=...

URLs or article identifiers when available

If you only have a product/topic query, start from a targeted official hub and discover linked Help articles from there

Agentforce queries: start from the Agentforce developer guide and follow linked Help articles

Messaging / Enhanced Web Chat queries: start from the Enhanced Web Chat docs or landing Help article, then follow one hop to child setup/security articles

Expect navigation shell noise and incomplete body extraction

Focus on retrieving the actual article body, not the rendered header/footer shell

Reject shell or soft-404 pages such as "We looked high and low but couldn't find that page"

Cross-check titles, product area, and article body before trusting a result

5. PDFs Are a Valid Official Fallback

Use PDFs when:

The guide has a stable official PDF

HTML extraction is inconsistent

A long-form developer guide is easier to search locally after normalization

PDFs may be stored

locally

and indexed later, but should

not

be committed into the public repo.

Answer Requirements

When using

sf-docs

, answers should include:

Source type

— qmd local hit, official HTML page, or official PDF

Guide/article name

Exact official URL

Any retrieval caveat

— for example, if fallback scraping was needed or if the content appeared partially rendered

If the evidence is weak, say so plainly.

Cross-Skill Integration

Skill

How

sf-docs

Helps

sf-ai-agentforce

Find Agentforce, PromptTemplate, Models API, and setup docs

sf-ai-agentscript

Find Agent Script syntax, CLI, and reasoning engine docs

sf-apex

Find Apex language and reference docs

sf-lwc

Find LWC guides, component references, and wire docs

sf-integration

Find REST, SOAP, Named Credential, and auth docs

sf-deploy

Find CLI, deployment, packaging, and metadata references

Delegation rule

If another skill needs authoritative Salesforce documentation, it should use sf-docs as the retrieval layer rather than improvising generic web search. Local Storage Policy sf-docs is part of the core skill suite qmd remains an optional external dependency Downloaded PDFs, scraped markdown, manifests, and indexes should live on the user's machine Official Salesforce docs content should not be stored in this public Git repository Default Local Corpus Layout Use a stable local root such as: ~/.sf-docs/ Recommended structure: ~/.sf-docs/manifest/ — discovery manifests and fetch/index status ~/.sf-docs/raw/pdf/ — downloaded official PDFs ~/.sf-docs/raw/html/ — optional raw HTML captures ~/.sf-docs/normalized/md/ — canonical markdown corpus for qmd indexing ~/.sf-docs/qmd/ — qmd-specific config notes ~/.sf-docs/logs/ — optional diagnostics and fetch logs Full reference: references/local-corpus-layout.md First-Version Behavior The initial implementation should optimize for correctness and operational simplicity: qmd-first when available Sequential fallback to Salesforce-aware scraping Targeted retrieval, not broad crawling, during normal lookups Grounded responses with official source links Query-Time Runtime Flow Detect qmd and local corpus availability Run qmd lookup if available Evaluate hit quality On weak/missing results, use Salesforce-specific HTML/PDF fallback Answer with source grounding and retrieval caveats when needed Full runtime guide: references/runtime-workflow.md Parallel qmd + scraping can be considered later if benchmarks justify the added complexity. Success Criteria sf-docs is successful when it does the following better than generic web search: Finds the right Salesforce page or PDF more often Avoids failed fetches on help.salesforce.com Reduces hallucinations by grounding on official sources Improves the documentation quality available to the rest of the sf-* skills References Document Purpose references/local-corpus-layout.md Local-only corpus structure and runtime detection rules references/discovery-manifest.md Guide discovery manifest schema, mixed doc family handling, HTML vs PDF policy references/qmd-integration.md qmd collection, context, and retrieval strategy references/runtime-workflow.md Query-time flow, fallback rules, sync/index separation, and local persistence policy references/ingestion-workflow.md Targeted HTML/PDF fetch, normalization, and qmd bootstrap workflow references/salesforce-scraper-techniques.md Salesforce-aware browser extraction techniques, Shadow DOM handling, and PDF fallback rationale references/pilot-scope.md Initial guide scope for v1 ingestion references/benchmark-protocol.md qmd-first and no-qmd validation protocol references/cli-workflow.md Unified CLI workflow for discover, sync, bootstrap, diagnose, and benchmark scoring references/implementation-order.md Recommended v1 execution order references/final-architecture.md Final architectural recommendation Assets & Scripts File Purpose assets/discovery-manifest.seed.json Starter guide manifest seed assets/retrieval-benchmark.json Expanded core retrieval benchmark cases for exact identifiers, guide routing, and evidence grounding assets/retrieval-benchmark.results-template.json Template for recording qmd-first and no-qmd core benchmark outcomes assets/retrieval-benchmark.robustness.json Negative / wrong-guide rejection benchmark for hardening fallback behavior assets/retrieval-benchmark.robustness.results-template.json Template for recording robustness benchmark outcomes scripts/cli.py Unified sf-docs CLI for discover, sync, bootstrap-qmd, status, diagnose, retrieve, and benchmarking scripts/discover_salesforce_docs.py Enrich guide seeds into a discovery manifest and optionally verify PDF candidates scripts/salesforce_dom_scraper.mjs Salesforce-aware browser scraper with Shadow DOM, legacy doc container, iframe, and help-page heuristics scripts/sync_sf_docs.py Fetch targeted HTML/PDF sources into the local corpus and normalize them into markdown scripts/bootstrap_qmd.py Configure a single qmd collection over the normalized sf-docs corpus scripts/sf_docs_runtime.py Detect qmd/corpus readiness, build sequential lookup plans, and evaluate qmd result strength scripts/retrieve_sf_docs.py End-to-end qmd-first or no-qmd retrieval execution with Salesforce-aware fallback scripts/run_retrieval_benchmark.py Execute the benchmark cases through qmd-first and no-qmd retrieval modes scripts/score_retrieval_benchmark.py Score benchmark results for qmd-first and no-qmd modes License MIT License. See LICENSE file in the repo root. Copyright (c) 2024–2026 Jag Valaiyapathy