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get_thought

Retrieve raw content from thought files in Project MCP for review and analysis of project documentation, plans, and task management data.

Instructions

Reads a specific thought file and returns its raw content for review.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileYesThe thought file to read (e.g., "my-ideas.md").
categoryNoThe category/subdirectory. Default: "todos".todos
from_archiveNoRead from archive instead of active thoughts. Default: false.
Behavior2/5

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

With no annotations provided, the description carries full burden but only states it 'reads' and 'returns raw content.' It doesn't disclose error behavior (e.g., if file doesn't exist), permission requirements, rate limits, or whether the operation is idempotent. For a read tool with zero annotation coverage, this leaves significant behavioral gaps.

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 a single, efficient sentence that front-loads the core action and outcome. Every word earns its place with no redundancy or fluff, making it easy to parse quickly.

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

Completeness3/5

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

For a read tool with 3 parameters and no output schema, the description is minimally adequate but lacks completeness. It doesn't explain the return format (e.g., text string, structured data) or error handling. With no annotations and no output schema, more context about behavior would be helpful despite the clear purpose.

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 fully documents all three parameters (file, category, from_archive). The description adds no parameter-specific information beyond what's in the schema, such as file format expectations or category options. Baseline 3 is appropriate when schema does the heavy lifting.

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?

The description clearly states the action ('Reads') and resource ('a specific thought file') with the outcome ('returns its raw content for review'). It distinguishes from siblings like 'list_thoughts' (which lists files) and 'process_thoughts' (which processes content), but doesn't explicitly contrast with 'get_doc' or 'get_task' which have similar 'get' patterns for different resources.

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

Usage Guidelines3/5

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

The description implies usage when raw content review is needed, but provides no explicit guidance on when to use this versus alternatives like 'get_doc' (for documents) or 'list_thoughts' (for metadata). It mentions 'for review' which suggests a human-facing use case, but lacks when-not scenarios or prerequisites.

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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