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process_thoughts

Reads brain dump markdown files, returning raw content and project context for analysis, so you can understand user intent, group related items, and create structured tasks. After task creation, the processed file is archived.

Instructions

Reads brain dump markdown files from .project/thoughts/todos/ and returns the content along with project context for analysis.

This tool gathers:

  1. Raw thought content - The unstructured brain dump as written

  2. Project context - Existing tasks, roadmap milestones, decisions for reference

  3. Task format guide - The YAML structure for creating tasks

YOU (the LLM) should then analyze the content to:

  • Understand the user's intent (explicit, shadow/underlying, practical)

  • Identify logical task groupings (consolidate related items)

  • Determine appropriate priorities based on context

  • Create well-structured tasks using create_task

  • After creating tasks, use archive_thought to archive the processed file

The tool does NOT automatically create tasks - it provides you with everything needed to make intelligent decisions about task creation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileNoSpecific thought file to process (e.g., "my-ideas.md"). If not provided, processes all files in thoughts/todos/.
projectYesProject prefix for task IDs when you create tasks (e.g., "AUTH", "API").
Behavior4/5

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

No annotations provided, so description bears full burden. It discloses read-only behavior (reads files) and that no automatic task creation occurs. Could mention if any side effects, but likely none.

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?

Well-structured with bullet points and clear sections. Front-loaded with main action. Some repetition in listing gathered items, but overall appropriately sized for complexity.

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

Completeness4/5

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

Covers what tool does, returns, and intended subsequent actions. Lacks explicit comparison to sibling tools like list_thoughts, but sufficient given the detailed workflow guidance. Output schema absent but not critical for this read-and-analyze tool.

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 descriptions already cover both parameters (file optional, project required) with examples. Description adds context about project as task ID prefix, but does not significantly enhance beyond schema's 100% coverage.

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 clearly states the tool reads brain dump markdown files and returns content with project context. It distinguishes from siblings like list_thoughts, get_thought, and archive_thought by explaining its analysis-oriented role.

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?

Explicitly outlines the workflow: analyze content, create tasks using create_task, then archive with archive_thought. It also states the tool does not auto-create tasks, setting clear expectations and alternatives.

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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