Data Hygiene for MCP: Making Tasks Readable for Assistants and Humans

Write better tasks that both AI assistants and humans can understand. This guide covers clear titles, descriptions, acceptance criteria, and comment conventions that dramatically improve MCP tool effectiveness and team collaboration.

Why Data Hygiene Matters for MCP

Well-structured tasks enable better MCP outcomes:

Benefits of Good Data Hygiene

Better tool results: AI assistants can parse and act on well-structured tasks
Accurate filtering: Clear titles and descriptions enable precise task searches
Automated workflows: Structured data enables reliable automation
Team clarity: Clear tasks reduce confusion and improve collaboration
Better reporting: Structured data produces more accurate status reports

Task Title Best Practices

Good vs Bad Titles

❌ Bad Title Examples

"Fix bug" (too vague)
"Update the thing" (unclear what "thing" is)
"ASAP!!!" (no actual information)
"Task 123" (not descriptive)

✓ Good Title Examples

"Fix authentication timeout error on login page"
"Update user profile API to include avatar field"
"Design mobile navigation menu for iOS app"
"Write documentation for payment processing flow"

Title Conventions

Title Format Guidelines

Start with action verb: Fix, Update, Create, Design, Write
Be specific: Include what, where, and context
Keep it concise: 50-80 characters ideal
Use consistent format: Follow team conventions
Avoid jargon: Use clear, understandable language

Task Description Patterns

Structured Description Template

Recommended Description Structure

## Context [Why this task exists, what problem it solves] ## Requirements [What needs to be done, specific requirements] ## Technical Details [Implementation notes, dependencies, constraints] ## References [Links to related tasks, docs, designs]

This structure: Makes it easy for both humans and AI to understand the task

Good Description Example

Example: Well-Structured Description

## Context Users are experiencing authentication timeouts when logging in during peak hours. This is causing support tickets and user frustration. ## Requirements - Increase session timeout from 15 minutes to 30 minutes - Add warning message 5 minutes before timeout - Log timeout events for monitoring ## Technical Details - Update session configuration in auth service - Modify frontend to show timeout warning - Add logging to analytics service - Related to task #456 (session management improvements) ## References - Design: [link to design doc] - API spec: [link to API docs] - Related task: #456

Why this works: Clear context, specific requirements, technical details, references

Acceptance Criteria Format

Clear acceptance criteria enable better MCP automation:

Acceptance Criteria Best Practices

Testable: Each criterion should be verifiable
Specific: Avoid vague statements like "works correctly"
Complete: Cover all requirements
Formatted consistently: Use checkboxes or numbered list

Acceptance Criteria Example

Example: Clear Acceptance Criteria

## Acceptance Criteria - [ ] Session timeout increased to 30 minutes (verified in config) - [ ] Warning message appears 5 minutes before timeout (tested in browser) - [ ] Warning message is dismissible and non-blocking - [ ] Timeout events are logged to analytics service (verified in logs) - [ ] Works on Chrome, Firefox, and Safari (tested on all browsers) - [ ] Mobile responsive (tested on iOS and Android)

Why this works: Testable, specific, complete, formatted consistently

Comment Conventions

Comment Types

Standard Comment Types

Progress updates: "Completed authentication service update"
Decisions: "Decision: Using JWT tokens instead of sessions"
Blockers: "Blocked: Waiting on API response from payment service"
Questions: "Question: Should we support SSO in this release?"
Context: "Context: This relates to the security audit requirements"

Comment Formatting

Recommended Comment Format

[Type]: [Brief summary] [Detailed explanation if needed] [Links or references]

Example:

Progress: Completed authentication service update Updated session timeout configuration and added logging. All tests passing. Related: PR #123, commit abc123

Impact on MCP Outcomes

Better Task Filtering

How Good Titles Help MCP

With clear titles, MCP tools can accurately filter tasks:

"List tasks about authentication" → Finds "Fix authentication timeout error" vs "List tasks about authentication" → Misses "Fix bug" (unclear title)

Better Task Creation

How Structured Descriptions Help

With structured descriptions, MCP can create better tasks:

"Create a task for fixing the login bug" → Creates task with: - Clear title: "Fix authentication timeout error on login page" - Structured description with context and requirements - Acceptance criteria based on description structure

Better Status Reports

How Good Data Enables Reporting

With consistent formatting, MCP can generate accurate reports:

Group tasks by project (clear project assignments)
Identify blockers (standardized blocker comments)
Track progress (consistent progress comment format)
Generate summaries (structured descriptions parse easily)

Data Hygiene Checklist

Task Quality Checklist

Title is clear and specific (50-80 characters)
Description includes context, requirements, and technical details
Acceptance criteria are testable and specific
Comments follow standard format (Type: Summary)
Task has clear assignee and due date
Task is linked to relevant project and related tasks

Best Practices

Data Hygiene Best Practices

Establish conventions: Document team standards for titles, descriptions, comments
Use templates: Create task templates with structured formats
Regular cleanup: Review and improve existing tasks periodically
Train team: Share best practices and examples
Enforce in prompts: Use MCP prompts that create well-structured tasks
Monitor quality: Track task quality metrics

Improve Your Task Data Quality

Write better tasks that both AI assistants and humans can understand and act on

Acceptance Criteria →Templates