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Read a workflow's collected data

writ_workflow_data
Read-onlyIdempotent

Read tabular data from a saved browser workflow. Filter results by query or run ID, and fetch full untruncated records using refs.

Instructions

Read the accumulated extracted data for a saved WORKFLOW as a table (columns + rows). Filter with q, or inspect one run with run_id. Long text cells arrive preview-cut (_truncated lists the fields) — hydrate full records via refs. NOTE: crawl ids are a different namespace — a writ_crawl_site run's data lives behind writ_crawl_status / writ_saved_crawl_data, not here.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoSubstring filter across fields.
refsNoHydration: fetch FULL untruncated records by ref '<run_id>:<record_index>' (both fields are on every row). Max 100.
viewNoall | latest | run
limitNo
deviceNoA linked Writ desktop's agent_id (writ_devices): act ON it. Omit to use the desktop this connection chose with writ_devices action='use' (if any).
outputNoRESPONSE SHAPE — set this whenever the answer is for a program or an API you are building, not for you to read. {shape: 'envelope' (default: Writ's full answer, projected) | 'table' ({columns, rows, total}) | 'records' (bare list of records) | 'record' (the newest record alone — one entity, a usage meter, a dashboard), fields: ['used', 'percent_used as pct', 'items.0.price as first_price'] (ordered pick, renames, dotted paths; missing → null so keys are stable), exclude: ['depth'], include_meta: false (page metadata content_kind/depth/thumbnails are STRIPPED unless true), key: 'usage' (wrap)}. On writ_crawl_site with save_as it is SAVED as the API's default shape.
run_idNo
workflowNo
workflow_idNo
preview_charsNoCut string cells to this many characters (default 2000; 0 = full cells).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds non-obvious behavior beyond them: text cells arrive preview-cut, `_truncated` lists the cut fields, and full records are hydrated via refs. It omits pagination/limit defaults and what `view` modes do, but the truncation-and-hydration disclosure is genuinely additive.

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?

Front-loaded with the core action, then filtering, then truncation/hydration behavior, closing with the namespace caveat. Every sentence carries load-bearing information and there is no restating of the title or schema.

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

Completeness4/5

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

For a 10-param tool with no output schema and a nested output object, the description covers the essential read path, truncation semantics, and cross-namespace disambiguation well. Gaps remain around the view/limit/device parameters and the saved-workflow concept, but nothing blocks a correct call.

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

Parameters3/5

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

Schema coverage is 60%, and the description meaningfully explains q, run_id and the refs hydration path (equivalent to '<run_id>:<record_index>'). However several parameters (view, limit, device, workflow/workflow_id) get no clarification beyond the schema, so it only partially compensates for the coverage gap.

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?

States a specific verb and resource ('Read the accumulated extracted data for a saved WORKFLOW as a table') and describes the output shape (columns + rows). The NOTE explicitly differentiates this from the crawl-data siblings (writ_crawl_status / writ_saved_crawl_data), so an agent can route without opening a schema.

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

Usage Guidelines4/5

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

Gives concrete routing guidance: 'Filter with `q`, or inspect one run with `run_id`', and the NOTE names the alternatives to use for crawl data with the condition that selects them. It stops short of contrasting with other plausible siblings like writ_search_data or writ_export_data.

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