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Glama

OneDrive Read File

onedrive_read_file
Read-only

Reads a text file from your OneDrive synced folder. Supports .txt, .md, .csv, .json, .xml, .log and several code file types. Auto-detects UTF-8, falls back to Latin-1/Windows-1252 for legacy files (common in Latin American banking .TXT padrones). For files elsewhere on this Mac, use file_read.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesAbsolute path to the file
offsetNoStart reading at byte offset (default 0)
encodingNoForce a specific encoding: 'auto' (default), 'utf8', 'latin1', 'cp1252', 'ascii', 'utf16'
max_bytesNoMaximum bytes to read (default 1048576 = 1 MB, capped at 10485760 = 10 MB)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesAbsolute path of the file
bytesYesTotal file size in bytes
offsetNoByte offset the read started at
contentYesDecoded file text content
encodingNoEncoding used to decode (utf8 | cp1252 | latin1 | ascii | utf16)
truncatedNoTrue if more content remains beyond what was returned
bytes_readNoNumber of bytes read in this slice

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the read-only behavior is covered. The description adds valuable behavioral context by explaining encoding auto-detection and fallback: 'Auto-detects UTF-8, falls back to Latin-1/Windows-1252 for legacy files.' This goes beyond what the annotations or schema communicate.

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 three sentences, front-loaded with the core purpose, then supporting details on formats and encoding, and ends with a concise pointer to the alternative. Every sentence adds value with no repetition or fluff.

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 the output schema exists and annotations cover safety, the description fully covers the relevant operational context: supported file types, encoding behavior, and scope limitation. It also names the sibling tool for out-of-scope files, making the tool's placement in the overall ecosystem clear.

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?

The schema already provides 100% coverage with descriptions for all four parameters, earning a baseline of 3. The description enhances parameter meaning by explaining the file type scope and the practical encoding fallback use case, which directly informs how to interpret 'encoding: auto' and the 'path' constraint.

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 opens with a specific verb and resource: 'Reads a text file from your OneDrive synced folder.' It clearly distinguishes itself from the sibling file_read tool by stating 'For files elsewhere on this Mac, use file_read,' and it lists supported file types, making its scope unambiguous.

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?

It explicitly states when to use this tool (files in the OneDrive synced folder) and when not to, with a direct alternative: 'For files elsewhere on this Mac, use file_read.' This satisfies the requirement for explicit usage guidance and alternative references.

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

A3.5/5.0
Disambiguation3/5

Many tools are clearly distinct per app (e.g., chrome_*, safari_*, m365_*), but there is notable overlap between generic file tools like `file_list` and `finder_list`, both listing files; `search_contacts` and `list_contacts` serve similar purposes; `report_friction` and `report_problem` both send feedback to the team. The large number of tools with similar purposes in different domains creates moderate ambiguity for an agent.

Naming Consistency4/5

The naming convention is very consistent overall: most tools follow a `{app}_action` or `verb_noun` pattern (e.g., `chrome_click`, `create_calendar_event`, `list_reminders`). There are minor deviations like `lmcp_install_upgrade` (two verbs) and `complete_omnifocus_task` vs. `complete_reminder` (inconsistent verb placement). Still, the pattern is predictable and readable across the full set.

Tool Count2/5

With 225 tools, the surface is extremely large and heavy. While it covers many distinct domains (browsers, mail, calendar, files, notes, reminders, video editing, web automation, etc.), the sheer number makes it hard to navigate and likely includes many rarely-used tools. This is far beyond the well-scoped range of 3-15 tools and feels excessive even for a 'local everything' MCP server.

Completeness3/5

For many app integrations, the tool set provides solid CRUD coverage (e.g., Calendar has create, read, update, delete; Apple Notes has create, read, update, list, search; OmniFocus has create, list, search, complete). However, some areas are incomplete: for example, there is no tool to create a new Mail folder or delete notes. The 'web' tools lack a clear update/delete for saved sessions. The suite is broad but has notable gaps within individual domains.