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performance

Generates 1:1 preps, summaries, and performance reviews from Jira and Azure DevOps delivery data.

4|Updated Mar 17, 2026
Search Tags:#feedback#engineering management#action items#jira#azure devops#performance review#1:1 prep
One-click install
npx skills add https://github.com/yeaboi-ai/yeaboi.ai --skill performance-yeaboi-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: performance
Source: https://github.com/yeaboi-ai/yeaboi.ai/tree/main/claude-plugin/yeaboi/skills/performance
Command: npx skills add https://github.com/yeaboi-ai/yeaboi.ai --skill performance-yeaboi-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Engineering leads spend hours preparing for 1:1s and writing performance reviews without easy access to the delivery data that should inform them. This Skill pulls real work history from Jira or Azure DevOps and turns it into 1:1 talking points, tracked action items, review drafts, and recorded observations. ## Core Features & Use Cases - 1:1 Preparation: Generates talking points, feedback, goals, and growth areas for an engineer, automatically folding in open action items from previous 1:1s. - 1:1 Summaries & Action Tracking: Converts pasted meeting notes into a structured summary with tracked action items carried into the next prep, with optional email delivery via configured SMTP. - Performance Reviews & Notes: Drafts periodic reviews (default six months) synthesizing past 1:1s, delivery history, and a competency framework, plus quick timestamped observations that feed future outputs. - Use Case: Before a weekly 1:1, ask for a prep on an engineer and receive data-grounded talking points scoped to the last two sprints of standups for a specific project. ## Quick Start Ask the assistant to prepare a 1:1 for a specific engineer using delivery data from the last two sprints.

Frequently Asked Questions about performance

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I prepare for a 1:1 with an engineer using delivery data?▼

Call perf_one_on_one_prep with the engineer's name from the roster. It generates talking points, feedback, goals, and growth areas from their Jira or Azure DevOps history, and automatically includes open action items from their previous 1:1.

How do I draft a performance review from Jira data?▼

Use perf_six_month_review with the engineer's name, optionally setting period_months for a different window. It synthesizes past 1:1s, delivery history, and the competency framework into a draft the lead should edit before use.

Can I scope 1:1 prep to a specific project or time period?▼

Yes. Pass a context spec like "standup,retro:1@2sprints project=apollo" plus project_label and tags. Run context_preview first to see how many sessions match before generating the output.

Why does the performance tool return an empty roster?▼

An empty roster means no issue tracker is configured, since engineers are derived from recent Jira or Azure DevOps assignees. Run yeaboi --setup to configure tracker credentials, then retry perf_roster.

What does llm_mode fallback mean in the output?▼

It means no LLM was reachable, so the artifact is a deterministic skeleton rather than a synthesized draft. Run yeaboi --setup to configure an API key and regenerate the output.

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