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 agentmods add skills/hoavdc/codexkit/codexkit-supplier-evaluationnpx skills add hoavdc/CodexKit --skill codexkit-supplier-evaluationgit clone --depth 1 https://github.com/hoavdc/CodexKitWrote 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/hoavdc/codexkit/codexkit-supplier-evaluation)<a href="https://agentmods.dev/skills/hoavdc/codexkit/codexkit-supplier-evaluation"><img src="https://agentmods.dev/badge/skills/hoavdc/codexkit/codexkit-supplier-evaluation.svg" alt="Measured on agentmods" 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 | $0.00059 | $0.01189 |
| Opus 5 | $0.00030 | $0.00594 |
| Sonnet 5 | $0.00012 | $0.00238 |
| Haiku 4.5 | $0.00006 | $0.00119 |
Grade A, and why
codexkit-supplier-evaluation 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 yesterday.
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 — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Supplier Evaluation Scorecard
When to Use
- During quarterly or annual supplier performance reviews
- When selecting vendors for new sourcing decisions
- When consolidating or rationalizing the supplier base
- When a supplier's performance triggers a review
Procedure
Step 1 — Define Evaluation Criteria
| Criterion | Weight | Measurement |
|---|---|---|
| Quality | 30% | Defect rate, inspection pass rate, returns |
| Delivery | 25% | On-time delivery %, lead time variance |
| Cost | 20% | Price competitiveness, total cost of ownership |
| Responsiveness | 15% | Communication speed, issue resolution time |
| Sustainability | 10% | ESG compliance, certifications, carbon footprint |
Adjust weights based on industry and strategic priorities.
Step 2 — Score Each Criterion
| Score | Level | Description |
|---|---|---|
| 5 | Excellent | Exceeds expectations consistently |
| 4 | Good | Meets expectations with occasional excellence |
| 3 | Acceptable | Meets minimum standards |
| 2 | Below Average | Frequent issues, requires monitoring |
| 1 | Unacceptable | Consistent failures, action required |
Step 3 — Calculate Weighted Total
Weighted Score = Σ (Score × Weight)
Step 4 — Tier Classification
| Weighted Score | Tier | Relationship Strategy |
|---|---|---|
| 4.5–5.0 | Strategic | Long-term partnership, innovation collaboration |
| 3.5–4.4 | Preferred | Stable relationship, volume commitment |
| 2.5–3.4 | Approved | Transactional, competitive bidding |
| < 2.5 | Conditional | Improvement plan required, phase-out risk |
Step 5 — Action Plan
For Conditional and low-Approved suppliers:
- Issue corrective action request (CAR)
- Define improvement targets with timeline
- Schedule re-evaluation in 90 days
- Identify backup supplier if no improvement
Inputs
| Input | Required | Format |
|---|---|---|
| Supplier name and category | Yes | Text |
| Performance data | Yes | Metrics per criterion |
| Contract/spend data | Recommended | Annual spend, contract terms |
| Previous evaluation | Recommended | Prior scorecard if available |
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.
- yesterday First seen · 145 lines · 59 tokens per session scan A ef801938d1cf
codexkit-supplier-evaluation is a skill published in the GitHub repository hoavdc/CodexKit (21 stars, last pushed 3mo ago), licensed MIT. It adds 59 tokens to every session and 1,189 once invoked, about $0.0003 per session on Opus 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.
Other skills, from other repositories
data_analyst
Analyses datasets with professional rigour — statistical summaries, clear narratives, and well-chosen visualisations.
reducing-aigc-detection
Systematically reduce AIGC detection rates in academic papers (Chinese/English). Analyzes detection reports, identifies high-impact sections, applies multi-layer rewriting strategies preserving formatting/footnotes, and verifies results. Supports 维普/知网/Turnitin platforms.
architecting-security
安全架构与治理：威胁建模 (STRIDE/PASTA/LINDDUN)、零信任身份架构、IAM/SSO/MFA/PAM、合规框架 (SOC2/PCI/HIPAA/GDPR)、DLP、隐私工程、安全控制设计。Use when designing security architecture, threat modeling new systems, implementing zero-trust identity, designing IAM/SSO/PAM, building compliance evidence chains, or planning privacy-by-design.
cultivating-personas
Distills AI agent voice patterns from conversation into a Persona Voice Card v1.0 (self/user/language/register/emojipolicy/flourish only — no judgment-shaped fields), validates schema + content safety + differentiation, and routes contributions through the existing submission portal. Use when the user wants to…
defending-applications
Application security defense knowledge for builders. Covers Web/API/GraphQL hardening (XSS/SQLi/SSRF/IDOR/BOLA/Mass Assignment/deserialization/upload/path traversal), authentication/authorization (OAuth 2.0/OIDC/JWT/Session/Cookie/SAML/SSO), and LLM application security (prompt injection, jailbreak, RAG poisoning…
detecting-and-responding
蓝队与紫队工程：检测规则编写、SIEM/EDR 调优、事件响应、数字取证、威胁狩猎、ATT&CK 映射、紫队演练闭环。Use when writing Sigma/YARA detection rules, tuning SIEM noise, responding to security incidents, conducting forensic analysis, hunting threats, or running purple team exercises.