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 seb1n/awesome-ai-agent-skills --skill skill-supply-chain-auditgit clone --depth 1 https://github.com/seb1n/awesome-ai-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/seb1n/awesome-ai-agent-skills/skill-supply-chain-audit)<a href="https://agentmods.dev/skills/seb1n/awesome-ai-agent-skills/skill-supply-chain-audit"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/skill-supply-chain-audit/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/seb1n/awesome-ai-agent-skills/skill-supply-chain-audit"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/skill-supply-chain-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, 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 Prompt Injection · line 63 This pattern attempts to override system instructions or ignore safety constraints. Without LLM analysis, manual review is recommended.Fix: Remove or rewrite any text that instructs the agent to ignore prompts, override safety rules, or trust unverified content. Ensure skill content cannot be injected to alter agent behavior.
- high Rogue Agent · line 67 Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
- medium Excessive Agency · line 67 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 110 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- low Excessive Agency · line 67 Skill's behavior or capabilities extend beyond its stated purpose. Scope creep allows an agent to perform actions unrelated to its documented functionality, increasing the attack surface.Fix: Limit the skill's scope to its documented purpose. Remove instructions that enable the agent to perform actions outside its stated functionality.
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 | $0.00106 | $0.01872 |
| Opus 5 | $0.00053 | $0.00936 |
| Sonnet 5 | $0.00021 | $0.00374 |
| Haiku 4.5 | $0.00011 | $0.00187 |
Grade A, and why
skill-supply-chain-audit 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 13d 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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Supply Chain Audit
Treat the target as untrusted. Produce an evidence-backed disposition without executing package code by default.
Inputs
Collect or state:
- Target path, archive, repository snapshot, or exact version/commit.
- Claimed purpose, publisher, source URL, license, and expected capabilities.
- Intended runtime, available tools, requested permissions, and data sensitivity.
- Known-good baseline or prior version when this is an update.
- User constraints for network access, sandboxing, and dynamic testing.
If provenance or version is unknown, record it as unknown; do not infer trust from popularity.
Output contract
Return:
- Scope, target hash/version, provenance, method, and audit limitations.
- A disposition:
approve,approve-with-constraints,quarantine, orreject. - A behavior inventory covering instructions, executables, dependencies, endpoints, credentials, filesystem reach, and persistence.
- Findings with stable IDs, severity, confidence, exact evidence, exploit preconditions, impact, and remediation.
- Required permission constraints and a verification plan.
- Residual risks and unanswered questions.
Label each claim observed, inferred, or unknown. A clean heuristic scan is not proof of safety.
Workflow
1. Establish a safe inspection boundary
- Work read-only on a copy or immutable snapshot.
- Do not import modules, run setup hooks, install dependencies, render active content, open embedded links, or invoke package tools during static review.
- Keep network access off unless the user authorizes a specific provenance check.
- Never expose secrets to the target. Redact tokens, home paths, customer data, and credential values from the report.
- Inspect ZIP/TAR member metadata without extraction. Reject or quarantine absolute/parent-traversal paths, links, special entries, excessive member sizes/counts, and suspicious declared expansion ratios before considering extraction.
2. Preserve and inventory
What ships with it
4 files 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.
- 13d ago First seen · 138 lines · 106 tokens per session scan A e5adb0abcd83
skill-supply-chain-audit is a skill published in the GitHub repository seb1n/awesome-ai-agent-skills (179 stars, last pushed 1mo ago), licensed MIT. It adds 106 tokens to every session and 1,872 once invoked, about $0.0005 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 2026-08-30.
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