Platform Data And Tooling API Context Get

Salesforce Data + Tooling API Skill

This skill provides field-level reference for 2130 standard Salesforce objects across two runtime API surfaces: the Enterprise/Data API (standard sObjects you query with SOQL and modify with DML) and the Tooling API (developer/metadata-adjacent records like ApexClass, ApexCodeCoverage, TraceFlag, and EntityDefinition).

Use it to look up authoritative field names, types, and properties before writing SOQL/SOSL, building DML, or reading records at runtime — so queries and writes don't fail with INVALID_FIELD / "No such column" errors.

Standard objects only. These assets cover standard sObjects and Tooling records. Custom __c objects, and custom __c fields on standard objects, are not in this corpus — they don't exist as static docs pages. For those, describe the live org instead (sf sobject describe --sobject <Name>).

Overview

Each object is documented as a JSON file with:

• Field definitions: name, type, and properties (Createable, Filterable, Groupable, Nillable, Sortable, Updateable)
• Relationship metadata (relationship name, referenced object, relationship type) for enterprise sObjects
• Supported SOAP calls and REST HTTP methods for Tooling records
• WSDL schema segment
• Usage notes and associated objects (enterprise sObjects)

This skill is for runtime data, not deployment. For authoring *-meta.xml source files (CustomObject, Flow, Profile, ...) use the Metadata API skill (platform-metadata-api-context-get). The two are companions, not substitutes.

How to Use This Skill

CRITICAL: Field-Existence Gate (do this BEFORE answering)

NEVER answer a field question — "does field X exist?", "is X filterable/sortable/groupable?", "what's X's API name/type?" — from memory or training data. This includes obvious system fields like Id, Name, CreatedDate, LastModifiedDate, OwnerId, IsDeleted. ALWAYS run the lookup first. You know these fields from training, but this skill exists precisely because your recollection of their properties (Filter/Sort/Group) and of which catalog documents them is unreliable. Confidence is not verification.

Run ONE atomic command that checks BOTH catalogs at once (a field can live in fields, in field_reference, or neither — see the dual-catalog note below):

jq '{fields: .fields["<FieldName>"], field_reference: .field_reference["<FieldName>"]}' assets/enterprise_api/<Object>.json
# e.g. checking CreatedDate on Account:
jq '{fields: .fields["CreatedDate"], field_reference: .field_reference["CreatedDate"]}' assets/enterprise_api/Account.json

Interpret the result: found in fields → use its properties for capability answers. Found only in field_reference → it exists, but Filter/Sort/Group cannot be determined from this skill (that catalog carries no property flags). null in both → not in this corpus (may still be a real live-org/custom field — describe the org).

MANDATORY VERIFICATION GATE. Before you state any field fact, you MUST first print this line verbatim in your reply to the user (like the metadata skill's status line):

field_lookup: object=<Object> field=<FieldName> checked_fields=<yes|no> checked_field_reference=<yes|no> result=<in_fields|in_field_reference|not_found>

If you cannot print this line truthfully with both checks = yes, you have not done the lookup — stop and run the jq command. Do not fabricate a citation like "based on the skill's data" without having run it.

This gate line is a self-verification marker for your conversational response only — do NOT write it into files you generate for the user (.soql, .md, .json, query comment headers, etc.). Deliverables should contain just the answer/query the user asked for; keep the field_lookup: line out of them.

CRITICAL: Section-Specific Consumption

ALWAYS consume only the specific sections you need from JSON files, NOT entire files.

For assets/enterprise_api/*.json and assets/tooling_api/*.json files, always use jq or programmatic JSON parsing to extract only the sections you need. Do not load these files whole via Read, cat, or read_file — they contain verbose wsdl_segment and field_reference sections that waste 60-80% of tokens on large sObjects like Account.

Each JSON file contains multiple sections. Most use cases only need 1-2:

• For query/DML field lists: load only the fields section
• For relationship traversal: load fields (the relationship_name / refers_to columns are inline)
• For Tooling call support: load supported_soap_calls / supported_rest_api_http_methods
• For "can this user query it?" / permission questions: load special_access_rules (present on both surfaces when the object documents access gates)
• For query ceilings / unsupported clauses (record caps, no ORDER BY/queryMore()/OFFSET): load limitations — present only on objects that impose them
• Skip by default: wsdl_segment, ispersonaccount_fields

Dual-catalog rule (imperative — this is the one people get wrong):

1. A field can be in fields, in field_reference, in both, or in neither. These are two DIFFERENT catalogs, not a superset relationship.
2. A miss in fields is NOT a "field doesn't exist" answer. Check field_reference too before concluding anything — the atomic jq command above does both in one shot.
3. Filter/Sort/Group/Create/Update/Nillable properties come only from fields. A field found only in field_reference has NO retrievable capability flags here — say so; don't guess.

<details>
<summary><b>Why the two catalogs differ (reference — optional reading)</b></summary>

fields comes from Salesforce's SOAP "Fields" table (query/DML properties: Create/Filter/Sort/Group/Update/Nillable). field_reference comes from a different UI-facing "Field List" table (label/length/precision/scale) that some objects document separately from the SOAP table — and it can include many fields fields never lists at all (e.g. objects with very large boolean-flag catalogs, or assorted admin-facing fields the SOAP table omits). Across the corpus, thousands of fields exist ONLY in field_reference, and a smaller number exist only in fields. This is why a field-existence answer requires checking both, and why capability questions can only be answered from fields.

</details>

Which folder?

• Standard sObjects you query and modify at runtime (Account, Contact, Opportunity, Lead, Case, ...) → assets/enterprise_api/
• Developer / diagnostics records (ApexClass, ApexCodeCoverageAggregate, TraceFlag, EntityDefinition, MetadataComponentDependency, SymbolTable) → assets/tooling_api/
• Custom __c objects and custom __c fields → NOT in these assets. Describe the live org: sf sobject describe --sobject <Name> --target-org <alias>. (A custom field like Region__c on standard Account won't be in assets/enterprise_api/Account.json either.)

Example Queries (Section-Specific)

Do:

• "Show me only the 'fields' section from assets/enterprise_api/Account.json"
• "What are the filterable fields on Opportunity?"
• "Which fields on Contact are relationships, and what do they refer to?"
• "What SOAP calls does ApexClass support in the Tooling API?"
• "Field X isn't in fields — check field_reference before saying it doesn't exist"

Don't:

• "Load Account.json" (pulls the huge wsdl_segment; load fields and field_reference separately instead of the whole file)

JSON File Structure

Enterprise (data) sObjects live in assets/enterprise_api/; Tooling records live in assets/tooling_api/. Both share a common core, with a few surface-specific sections.

{
  "sections": ["title", "description", "fields", "wsdl_segment", ...],
  "title": "Account | Enterprise API",
  "description": "Plain-text description of the object.",
  "fields_columns": ["type", "properties", "description", "relationship_name", "refers_to", "relationship_type"],
  "fields": {
    "fieldName": {
      "type": "string | reference | picklist | ...",
      "properties": "Create, Filter, Group, Nillable, Sort, Update",
      "description": "Field description",
      "relationship_name": "(reference fields only)",
      "refers_to": "(reference fields only) e.g. Account"
    }
  },
  "wsdl_segment": "<xsd:complexType>...</xsd:complexType>"
}

fields is a dict keyed by field API name (e.g. fields["AnnualRevenue"]), not a list — iterate with .items()/.keys(), don't index it positionally.

How sections are derived (read this before assuming a section list)

Each JSON file is generated from whatever ## Heading sections actually appear on that object's Salesforce docs page — the JSON schema is not a fixed, uniform template applied identically to every object. Two consequences follow directly from that:

1. No section is guaranteed present on every object, fields included. A section exists in a file only if the source docs page had a matching heading. Some Tooling docs pages have no fields table at all (thin/beta pages), so fields can be missing; a small number of SOAP-header-style pages label their field table singular (field) instead of plural. Always check the file's own sections array (or "fields" in sections) before assuming a section exists — don't hard code an expectation from having looked at one or two example objects.
2. A page can carry extra sections beyond the common ones, one per additional ## heading Salesforce's docs used on that specific page (e.g. a nested complex type referenced by a field, like a picklist's value-metadata description, or a record-type-info block). These are normalized into snake_case keys and stored either as their own top-level section, or — when the converter recognizes the heading as a distinct sub-type rather than a plain content section — nested under a sub_types dict keyed by the sub-type's name. Treat the "Available Sections" list below as the common/frequent case, not an exhaustive enum — the authoritative list for any one object is that object's own sections array.

Available Sections (common case — not exhaustive; see above)

• title, description, fields_columns: present on essentially all objects
• fields: present on the large majority of objects, but see point 1 above — verify via sections rather than assuming
• Enterprise-only: usage, associated_objects, ispersonaccount_fields, field_reference, field_reference_columns
• Tooling-only: supported_soap_calls, supported_rest_api_http_methods
• special_access_rules: who can query/access the object and any permission or license gate (e.g. "Customer Portal users can't access this object", "requires Omnistudio licenses"). Present on both surfaces. Read this before concluding a query will run for a given user — it's a query-eligibility fact no field flag captures.
• limitations: query ceilings and unsupported SOQL clauses the object imposes (e.g. MetadataComponentDependency: max 2000 records via Tooling API / 100,000 via Bulk API 2.0; ORDER BY, OFFSET, queryMore(), and *Name-field filters are not supported). Read this before writing a query against an object that has it — these constraints are not derivable from the fields properties.
• wsdl_segment: schema definition (verbose — skip unless you need the raw type)
• sub_types and any other snake_case-named section not listed above: object-specific nested schema description, present only when that object's docs page had a matching heading — inspect the file's sections array to discover them per-object

The fields_columns array tells you which columns each object's fields entries carry — check it per-object rather than assuming a fixed shape. Enterprise sObjects typically add relationship_name, refers_to, and relationship_type; Tooling records typically carry only type, properties, description — but a meaningful minority of Tooling objects also carry relationship_type, so don't treat it as enterprise-exclusive. relationship_type values also have spelling variants in the source data (e.g. "Lookup" vs. "Look up") — compare loosely (e.g. .replace(" ", "").lower()) rather than exact string equality.

Type strings are case-inconsistent across objects — do not assume a single casing. The same concept appears under multiple castings depending on the source doc page: string/String, boolean/Boolean, dateTime/DateTime/datetime. Compare type values case-insensitively (e.g. .lower()) rather than with == against one casing. Beyond the common string | reference | picklist types, real data also includes int, boolean, double, currency, date, dateTime, textarea, address, url, phone, email, time, anyType, base64, and others — treat the type list as open-ended.

A field can lack structured type/properties even when the object otherwise has them — check description as a fallback before concluding the data is missing. Because each object's JSON is generated from that object's own docs page, a page that presents a field's type/properties as prose ("Type: ... Properties: ... Description: ...") inside a single description paragraph — rather than as separate table columns — produces a fields entry with type/properties empty and that prose stuffed into description. This shows up for a range of reasons (generic template pages reused across many standard objects, e.g. history/share/feed-tracking companion objects) and can affect anywhere from one field to every field on an object — in the worst case fields_columns itself may say only ["description"]. If type/properties is empty or fields_columns looks suspiciously thin, check whether description starts with "Type: " and parse it as a fallback before concluding the field/object has no type information.

Picklist allowed values sometimes appear in description prose — check before assuming they're absent. No fields entry has a structured picklistValues list. Whether a picklist's allowed values are enumerated in description (as "Possible values are: ..." followed by the values) depends entirely on whether the source docs page enumerated them for that specific field — many do, many don't (e.g. org-configurable picklists backed by a separate value-set object typically only give illustrative examples like "such as New, Closed, or Escalated" instead of a full list). When present, the format itself is inconsistent — sometimes bare space/comma-separated tokens, sometimes Value—explanation em-dash pairs per line — so there's no single reliable regex; extract the substring after "Possible values are:" and parse case-by-case, and don't assume every picklist has a discoverable value set here.

A field's description may reference a relationship (e.g. "this is a dependent picklist", "this field controls X") without naming or resolving the other side of that relationship — the enterprise sObject's own fields section is not always where that answer lives. The Tooling API side of this dataset documents Salesforce's field-metadata objects (schema-about-schema, e.g. an object exposing per-field describe-style attributes) which can carry structured attributes — like a controlling field's identity for a dependent picklist — that the enterprise sObject's docs page never named explicitly. If an enterprise field's description points at a relationship it doesn't resolve, check whether a Tooling-side field-metadata object answers it before concluding the data doesn't exist anywhere in this skill.

A given object's JSON can carry sections beyond the common list above — inspect that object's own sections array rather than assuming a closed set. Any additional ## heading on the source docs page becomes its own snake_case-named section (or, when the converter recognizes it as a distinct nested type, a sub_types entry). These appear only on the specific objects whose docs happened to include that heading — a per-object schema-description payload, not junk to ignore. There's no fixed enumeration of every possible extra section name; discover them per-object via sections.

See the Index Table for the full object listing and per-object extra sections — it's ~125 KB, so grep -i "<ObjectName>" it for a single lookup rather than reading the whole file.

More detail: worked query/DML examples, relationship-traversal patterns, and a full section glossary live in references/usage_guide.md. Load it with the Read tool only when needed.