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Calera Infinite Context (ICX) — Persistent Memory & Associative Recall

Get Connected Document Content

icx_get_connector_document
Read-only

Retrieves the full on-demand text, markdown, or code content of a connected document, file, page, or issue from external services (Google Drive doc, Notion page, GitHub file, GitLab file, Linear ticket). Read-only operation. Requires X-License-Key authentication.

Input Schema

NameRequiredDescriptionDefault
typeNoOptional connector source type: 'gdrive', 'notion', 'github', 'gitlab', or 'linear' (used when connector_id is omitted).
resource_idYesThe file path (GitHub/GitLab), page UUID (Notion), issue key/ID (Linear), or file ID (Google Drive).
connector_idNoOptional specific connector ID. If omitted, the first active matching connector will be used.

Output Schema

NameRequiredDescriptionDefault
lengthYesdescription=Character length of content
statusYesdescription=Fetch status (VERIFIED_FETCHED | error)
contentYesdescription=Verbatim markdown or code document content
resource_idYesdescription=Resource or file identifier
connector_idYesdescription=Resolved connector ID
connector_typeYesdescription=Resolved connector type

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Beyond the 'readOnlyHint' annotation, the description explicitly defines the return types ('full on-demand text, markdown, or code content') and specifies the required authentication key, adding valuable operational 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?

The description is extremely concise. It achieves high information density in just two sentences, front-loading the capabilities and then detailing the operational requirements.

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?

Given that it has an output schema and the input schema is complete, the description covers all necessary context: what it does, where it gets data from, how it is authenticated, and its read-only nature. It is complete.

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 description coverage is 100%, so the schema defines the parameters well. The description primarily complements the schema by defining the specific resource identifiers (e.g., UUID for Notion, file path for GitHub). Given 100% coverage, a baseline score 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?

Explicitly states the verb 'Retrieves' and the resource type (connected documents). It details that it works across multiple external services (Google Drive, Notion, GitHub, etc.), making its purpose very clear.

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 clearly identifies the operation as 'Read-only' and specifies the necessary authentication ('Requires X-License-Key authentication'). While it doesn't explicitly rule out other document-reading tools, the clear focus on specific 'connected' sources provides strong usage guidance.

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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