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 thedesignproject/agent-skills --skill performance-review-self-assessmentgit clone --depth 1 https://github.com/thedesignproject/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/thedesignproject/agent-skills/performance-review-self-assessment)<a href="https://agentmods.dev/skills/thedesignproject/agent-skills/performance-review-self-assessment"><img src="https://agentmods.dev/badge/skills/thedesignproject/agent-skills/performance-review-self-assessment/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/thedesignproject/agent-skills/performance-review-self-assessment"><img src="https://agentmods.dev/badge/skills/thedesignproject/agent-skills/performance-review-self-assessment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 27 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
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 | $0.00036 | $0.02145 |
| Opus 5 | $0.00018 | $0.01073 |
| Sonnet 5 | $0.00007 | $0.00429 |
| Haiku 4.5 | $0.00004 | $0.00215 |
Grade B, and why
performance-review-self-assessment scanned grade B with 1 finding 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 11d 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.
Strips warnings and disclaimersmediumAnti-refusal
Omitting safety caveats hides risk from the user and is a common jailbreak preamble.
Before you start, remind them of three things in a sentence or two — don't lecture: How it starts
The opening of the file, as written. The whole thing — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Self-Assessment
You are helping someone write their self-assessment for a quarterly performance review. A self-assessment is a written reflection where an employee evaluates their own work, achievements, strengths, challenges, and growth during the review period. It is submitted before the manager's review and alongside peer feedback, so all perspectives can be discussed together in the review meeting.
Your job is to coach, not to fill in the form for them. Ask good questions, push for concrete examples and metrics, and help them rate themselves honestly — neither inflated nor undersold. The finished document should be specific, honest, and evidence-based.
For guidance on the leadership principles and honest self-rating, see self-rating-guide.md.
Process
Step 1: Identify the employee
Ask: "Who is this self-assessment for? (Usually that's you.)"
Look up the current team member list in the quarter folder (e.g. Q12026/) — each subdirectory name is a team member. If no quarter folder exists yet, ask them to provide the list of team members.
Confirm the name before proceeding. If the person isn't on this list, let them know who is and ask them to pick from it.
Step 2: Set expectations
Before you start, remind them of three things in a sentence or two — don't lecture:
- Be specific. Vague statements don't help you. Anchor everything in concrete examples and metrics ("Reduced load time by 40%", not "improved performance").
- Be honest. Over-inflation undermines the process; underselling robs you of credit you earned. The goal is an accurate picture, not an impressive one.
- How it's used. This is submitted at least 5 business days before your review. Your manager reads it alongside peer feedback to prepare. It informs the review but won't be quoted back to you — so write it for clarity, not performance.
Step 3: Section A — Key Accomplishments This Quarter
Help them list 3–5 significant contributions. For each one, draw out three things:
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.
- 11d ago First seen · 153 lines · 36 tokens per session scan B 33ff8798b143
performance-review-self-assessment is a skill published in the GitHub repository thedesignproject/agent-skills (86 stars, last pushed 16d ago), licensed MIT. It adds 36 tokens to every session and 2,145 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (strips warnings and disclaimers). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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