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by SoulNassim
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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workspace_read

Read a workspace file, including Markdown and YAML front matter, to inspect project content and guide coding-agent edits.

Instructions

Read a workspace file (Markdown, YAML front matter included).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "path": "<path>"
    },
    "name": "workspace_read"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYesPath relative to the workspace root.
projectNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv3.3.0

TDQS

C2.9/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full burden. It does disclose one behavior beyond the name: YAML front matter is included in the read output, which tells the agent to expect raw file content rather than parsed metadata. It says nothing about missing-file errors, permissions, binary files, or size limits.

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

Conciseness4/5

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

One short sentence, front-loaded with the verb and resource, with the clarifying parenthetical immediately after. It is efficient, though its brevity edges into under-specification rather than tightness.

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

Completeness2/5

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

For a read tool with no annotations, no output schema, and an undocumented 'project' parameter, the description should say more about return shape and failure behavior. As written, an agent knows it reads a file but not how to interpret 'project' or what happens on error.

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

Parameters2/5

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

Schema coverage is 50%: 'path' is documented as relative to the workspace root, but 'project' has no description anywhere. The tool description adds no parameter meaning, such as how 'project' scopes the path or whether it is required for certain workspaces.

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

Purpose4/5

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

States a specific verb (read) and resource (workspace file), and the parenthetical clarifies that Markdown with YAML front matter is returned intact. It does not, however, distinguish itself from siblings like workspace_list or workspace_overview, so an agent must infer the file-vs-listing split.

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

Usage Guidelines2/5

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

There is no statement of when to use this instead of workspace_list, workspace_overview, or open_glob, and no prerequisites or exclusions. The only guidance is implicit in the word 'file'.

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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