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Get persisted document content

claix.window_context.get
Read-onlyIdempotent

Retrieve raw content and metadata from a persisted document (GET /window-context/{document_id}). Requires document_id from an extraction with window_context. Returns success, document_id, file_name, schema_id, processed_at, and content. Free call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNoAPI key secreta de Claix. Ejemplo: claix_sk_abc123.... Opcional si la conexión MCP envía x-api-key en cabecera HTTP (recomendado en Smithery/Cursor).
document_idYesUUID del documento persistido (document_id de una extracción con window_context). Ejemplo: 3c7a9f21-4b8e-4d1a-9c6f-2e0d8a5b7c4f.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoJSON payload from the Claix API (extracted records, schema list, or Excel export metadata).
errorNoHuman-readable error message when success is false.
successYesTrue when Claix returned a successful response. False when isError is set on the tool result.

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safe-read nature is covered. The description adds the GET endpoint, persisted-document scope, and 'Free call' note, but it does not describe rate limits, auth-failure behavior, or other side effects. This adds some value but not rich behavioral context.

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?

Three short sentences front-load the core action and endpoint, then provide prerequisites, return fields, and cost. There is no filler or redundant repetition of schema details.

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?

For a single-required-parameter GET tool, the description combined with full schema coverage, rich annotations, and an output schema is sufficient. An agent knows what it retrieves, where the ID comes from, what it returns, and that the call is safe and free.

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?

The input schema already documents both parameters with descriptions and an example, and it already states that document_id comes from a window_context extraction. The description therefore adds no new parameter meaning beyond what the schema provides; with 100% schema coverage, the baseline of 3 is appropriate.

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 names a specific verb ('Retrieve'), a concrete resource ('persisted document'), and an endpoint ('GET /window-context/{document_id}'), and lists the exact return fields. This clearly distinguishes it from extract.* siblings and from claix.window_context.ask.

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?

It gives a clear precondition: document_id must come from an extraction with window_context, and it notes the call is free. It does not explicitly name alternatives or state when not to use it, but the context is clear enough for an agent to decide.

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

A3.9/5.0
Disambiguation5/5

Every tool has a clearly distinct role: extract.* produces raw structured JSON, agent.* adds agent-mode reasoning, schemas.* manages schemas, and window_context.* handles persisted documents. Even the parallel extract/agent pairs for each format are disambiguated by the agent/group prefix and explicit descriptions about is_agent_mode.

Naming Consistency4/5

All tools follow a claix.<group>.<target> convention with lowercase snake_case, which is predictable and readable. The main inconsistency is action placement: extract.doc is verb-first while schemas.create is object-first, and convert.json_to_excel uses a noun phrase instead of a verb.

Tool Count4/5

At 17 tools, the set is slightly above the ideal 3-15 range, but each tool maps to a distinct endpoint or format variant. The parallel extract and agent families are justified by different processing modes, though they do make the surface feel a bit heavier than necessary.

Completeness4/5

The set covers schema lifecycle (create, list, delete), extraction for five major formats, agent-mode variants, document deletion, and window-context query/retrieval. Minor gaps include no schema update endpoint and no generic document listing/retrieval outside window_context.

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