Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add latestaiagents/agent-skills --skill performance-review-assistantgit clone --depth 1 https://github.com/latestaiagents/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/latestaiagents/agent-skills/performance-review-assistant)<a href="https://agentmods.dev/skills/latestaiagents/agent-skills/performance-review-assistant"><img src="https://agentmods.dev/badge/skills/latestaiagents/agent-skills/performance-review-assistant/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/latestaiagents/agent-skills/performance-review-assistant"><img src="https://agentmods.dev/badge/skills/latestaiagents/agent-skills/performance-review-assistant.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00053 | $0.01564 |
| Opus 5.5 | $0.00021 | $0.00626 |
| Sonnet 5.5 | $0.00011 | $0.00313 |
| Haiku 4.5 | $0.00005 | $0.00156 |
Grade A, and why
performance-review-assistant scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 213 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Review Assistant
Write effective performance reviews that drive growth and development.
When to Use
- Writing quarterly or annual reviews
- Preparing for performance conversations
- Documenting feedback throughout the year
- Calibrating performance across teams
- Developing improvement plans
Review Structure
Standard Performance Review
# Performance Review: [Employee Name]
**Review Period:** [Start Date] - [End Date]
**Reviewer:** [Manager Name]
**Date:** [Review Date]
## Overall Performance Summary
[2-3 sentences summarizing overall performance and impact]
## Key Accomplishments
1. [Specific achievement with measurable impact]
2. [Another achievement with context]
3. [Third achievement]
## Areas of Strength
- [Strength 1 with specific example]
- [Strength 2 with specific example]
## Areas for Development
- [Development area 1 with specific example and suggestion]
- [Development area 2 with specific example and suggestion]
## Goals for Next Period
1. [SMART goal 1]
2. [SMART goal 2]
3. [SMART goal 3]
## Overall Rating
[Rating according to company scale]
Writing Effective Feedback
The SBI Model (Situation-Behavior-Impact)
**Situation:** During the Q3 product launch...
**Behavior:** You proactively identified a critical dependency issue and coordinated with three teams to resolve it before it impacted the timeline.
**Impact:** This saved an estimated two weeks of delay and demonstrated strong cross-functional leadership.
Examples of Good vs Poor Feedback
Vague (Poor):
"Sarah is a great team player and always positive."
Specific (Good):
"Sarah consistently supports her teammates. When the backend team was behind on the API integration, she volunteered to help debug issues despite her own full workload. This collaboration helped the team deliver on time."
Vague (Poor):
"John needs to improve his communication."
Specific (Good):
"John would benefit from providing more context in written updates. In the Q2 project update, stakeholders had questions that could have been preemptively addressed. I recommend using a structured format that includes status, blockers, and next steps."
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 213 lines · 53 tokens per session scan A 91cceaf80a5d
performance-review-assistant is a skill published in the GitHub repository latestaiagents/agent-skills (6 stars, last pushed 6mo ago), licensed MIT. It adds 53 tokens to every session and 1,564 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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