Extend MCP

Detect PDF form fields / generate an edit schema

detect_form_fields

Detect the fillable fields in a PDF form and return an edit schema (edit group): each property is a detected field with its type (text/checkbox/radio/dropdown/signature/table), page index, and bounding box. Use it to see what a form asks for, or as the scaffold for a structured fill — set extend_edit:value on each field and pass the populated schema to edit_pdf. Pass inputSchema to re-run detection against an existing schema (mapping mode) — for the edit-schema rules, call get_documentation with https://docs.extend.ai/editing/configuration.md first. Inspect runs with get_form_detection_run. Follow any llmContext guidance included in results.

Input Schema

TableJSON Schema

Name	Required	Description
`file`	Yes	The form PDF. Exactly one of id/url — e.g. { "url": "https://..." } or { "id": "file_..." }, never a bare string.
`environment`	Yes	"TEST" = the Test (development) environment, "PRODUCTION" = live. Must match a granted target from get_me (an API key pins one environment).
`inputSchema`	No	Existing edit schema to map against.
`waitSeconds`	No	Max seconds to block waiting on the run (clamped to the server wait budget).
`workspaceId`	Yes	Target workspace (ws_...). Must be a granted workspace — get_me lists the accepted values.
`instructions`	No	Guidance for schema generation.
`advancedOptions`	No	{ tableParsingEnabled?, radioEnumsEnabled?, nativeFieldsOnly?, conditionalGenerationEnabled? }

Output Schema

TableJSON Schema

Name	Required	Description
`runId`	Yes
`output`	No	Detected edit schema (PROCESSED only).
`status`	Yes	PROCESSING \| PROCESSED \| FAILED, or "running" (resume via the get tool).
`metrics`	No
`runType`	No
`llmContext`	No
`failureReason`	No
`failureMessage`	No

TDQS

A4.9/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses behavior beyond annotations by explaining the returned schema structure, the mapping-mode behavior of inputSchema, the existence of inspectable runs via get_form_detection_run, and that llmContext guidance may appear in results. This meaningfully complements the sparse annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but not bloated: it front-loads the core purpose and return contract, then gives crisp workflow guidance, documentation pointers, and run inspection. Every sentence contributes actionable information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having 7 parameters and nested objects, the description is complete enough: the schema handles parameter details, an output schema exists, and the description covers the main use cases, mapping mode, documentation lookup, run inspection, and result guidance. No critical behavioral context is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds extra value by explaining that inputSchema triggers mapping mode and by clarifying how detected fields and extend_edit values connect to edit_pdf. This goes beyond the schema's own descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('detect'), a clear resource ('fillable fields in a PDF form'), and the exact deliverable ('return an edit schema (edit group)'). It differentiates the tool from siblings by scoping it to form-field detection rather than extraction, splitting, or editing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit usage context: use it to see what a form asks for, as a scaffold for a structured fill, and in mapping mode with an existing inputSchema. It also names the relevant downstream/alternative tools: edit_pdf, get_form_detection_run, and get_documentation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4/5.0

Disambiguation5/5

Each tool targets a distinct resource+action combination, and the descriptions actively disambiguate potential overlaps (e.g., extract_data vs parse_document, detect_form_fields vs edit_pdf, get_file vs get_file_upload). The consistent verb_noun prefix pattern makes the semantic boundary of every tool immediately recognizable.

Naming Consistency4/5

The dominant verb_noun pattern is highly consistent across all nine domains (list_*, get_*, create_*, update_*, delete_*, run_*, get_*_run, get_*_batch, publish_*_version). Minor deviations exist: deploy_workflow_version vs publish_*_version for the same freeze-a-draft concept, and get_form_detection_run doesn't mirror its detect_form_fields counterpart.

Tool Count2/5

86 tools is a very heavy agent-facing surface, well past the 25+ threshold. The count is inflated by the near-identical 13-tool lifecycle repeated across extract, classify, and split (each with list/get/create/update/publish/runs/batches/versions), and while each tool has a distinct purpose, the sheer volume makes selection harder.

Completeness4/5

Core lifecycles are thoroughly covered: create → update → publish → run (single and batch) → poll → cancel → delete-run → list runs/versions. Notable gaps include no delete tool for extractors, classifiers, splitters, workflows, or evaluation sets, and edit/form-detection runs have no list endpoint (documented workaround: keep run IDs). These are hygenic gaps that don't block primary workflows.

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