Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/WARROOM-CEO/COREnpx agentmods add skills/warroom-ceo/core/performance-reviewWrote 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/warroom-ceo/core/performance-review)<a href="https://agentmods.dev/skills/warroom-ceo/core/performance-review"><img src="https://agentmods.dev/badge/skills/warroom-ceo/core/performance-review/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/warroom-ceo/core/performance-review"><img src="https://agentmods.dev/badge/skills/warroom-ceo/core/performance-review.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 | $0.00069 | $0.01178 |
| Opus 5.5 | $0.00028 | $0.00471 |
| Sonnet 5.5 | $0.00014 | $0.00236 |
| Haiku 4.5 | $0.00007 | $0.00118 |
Grade A, and why
performance-review-th 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Language: All user-facing output — responses, summaries, and any text the user will read — must be written in Thai (ภาษาไทย). Internal logic, file paths, code snippets, and technical values remain in English.
/performance-review-th
If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.
Generate performance review templates and help structure feedback.
Usage
/performance-review $ARGUMENTS
Modes
/performance-review self-assessment # Generate self-assessment template
/performance-review manager [employee] # Manager review template for a specific person
/performance-review calibration # Calibration prep document
If no mode is specified, ask what type of review they need.
Output — Self-Assessment Template
## Self-Assessment: [Review Period]
### Key Accomplishments
[List your top 3-5 accomplishments this period. For each, describe the situation, your contribution, and the impact.]
1. **[Accomplishment]**
- Situation: [Context]
- Contribution: [What you did]
- Impact: [Measurable result]
### Goals Review
| Goal | Status | Evidence |
|------|--------|----------|
| [Goal from last period] | Met / Exceeded / Missed | [How you know]-th |
### Growth Areas
[Where did you grow? New skills, expanded scope, leadership moments.]
### Challenges
[What was hard? What would you do differently?]
### Goals for Next Period
1. [Goal — specific and measurable]
2. [Goal]
3. [Goal]
### Feedback for Manager
[How can your manager better support you?]
Output — Manager Review
## Performance Review: [Employee Name]
**Period:** [Date range] | **Manager:** [Your name]
### Overall Rating: [Exceeds / Meets / Below-th Expectations]
### Performance Summary
[2-3 sentence overall assessment]
### Key Strengths
- [Strength with specific example]
- [Strength with specific example]
### Areas for Development
- [Area with specific, actionable guidance]
- [Area with specific, actionable guidance]
### Goal Achievement
| Goal | Rating | Comments |
|------|--------|----------|
| [Goal] | [Rating] | [Specific observations] |
### Impact and Contributions
[Describe their biggest contributions and impact on the team/org]
### Development Plan
| Skill | Current | Target | Actions |
|-------|---------|--------|---------|
| [Skill] | [Level] | [Level] | [How to get there] |
### Compensation Recommendation
[Promotion / Equity refresh / Adjustment / No change — with-th justification]
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 152 lines · 69 tokens per session scan A ad026f54a5d3
performance-review-th is a skill published in the GitHub repository WARROOM-CEO/CORE (30 stars, last pushed 6mo ago), licensed MIT. It adds 69 tokens to every session and 1,178 once invoked, about $0.0003 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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