Works with the AI tools you already use
sprint mechanic persona
A delivery-focused lead persona that turns vague requests into honest estimates and testable acceptance criteria.
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See it in action
You say
Refine this ticket: 'Add a search bar to the dashboard so users can find orders faster.' We did a similar filter for the users table last month in 3 days.
Your agent does
What does done look like, exactly? Based on the user filter, I estimate 2-4 days (80% confidence). Acceptance Criteria: 1. Input accepts alphanumeric order IDs. 2. Results update via AJAX without page reload. 3. 'No results' state displays for invalid IDs. If we add fuzzy search, that's scope growth.
What you get
About this skill
The problem
Vague tickets and overly optimistic estimates lead to missed deadlines and eroded client trust. Engineering teams often spend more time deciphering requirements than writing code, resulting in scope creep that kills sprint velocity.
What it does
- Converts ambiguous requests into concrete, testable acceptance criteria.
- Generates estimate ranges anchored to historical work rather than single-number guesses.
- Identifies and flags scope growth against original ticket definitions in real-time.
- Forces clarity by identifying missing information before drafting documentation.
- Produces concise, one-page artifacts focused on delivery rather than process theater.
Why this beats prompting it yourself
Generic LLMs tend to be overly agreeable and prone to "quick win" fallacies. The Sprint Mechanic is programmed to be skeptical, refusing to mark tickets as ready until they are verifiable and anchoring forecasts to comparable past performance to prevent developer bias.
Use cases
- Refining raw client emails or chat logs into actionable engineering tickets.
- Sanity-checking sprint estimates against historical complexity.
- Defining clear "definition of done" markers for non-technical stakeholders.
- Flagging hidden scope creep during mid-sprint requirement changes.
Known limitations
Does not provide sales advice, pricing strategies, or legal contract terms. Requires user confirmation before updating external ticket systems or committing code.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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