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 stacklok/toolhive-catalog --skill skillgit clone --depth 1 https://github.com/stacklok/toolhive-catalogWrote 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/stacklok/toolhive-catalog/skill)<a href="https://agentmods.dev/skills/stacklok/toolhive-catalog/skill"><img src="https://agentmods.dev/badge/skills/stacklok/toolhive-catalog/skill/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/stacklok/toolhive-catalog/skill"><img src="https://agentmods.dev/badge/skills/stacklok/toolhive-catalog/skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00108 | $0.01775 |
| Opus 5.5 | $0.00043 | $0.00710 |
| Sonnet 5.5 | $0.00022 | $0.00355 |
| Haiku 4.5 | $0.00011 | $0.00178 |
Grade A, and why
ci-agent-hardening scanned grade A 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 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
Every attack in the hackerbot-claw campaign depended on `curl` to `hackmoltrepeat.com`. Consider: How it starts
The opening of the file, as written. The whole thing — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CI Agent Hardening
Audit and fix security vulnerabilities in GitHub Actions workflows, with emphasis on AI-powered CI/CD. Based on two major 2026 incidents:
- Clinejection — Prompt injection in AI triage bot led to cache poisoning, credential theft, malicious npm publish (~4,000 developers affected)
- hackerbot-claw — Autonomous AI bot exploited 7 repos (Microsoft, DataDog, CNCF, Aqua Trivy), achieving full repo compromise on Trivy (25k+ stars) via PAT theft
Prerequisites
- Repository with
.github/workflows/directory bashavailable for running the audit script
Instructions
For background and exploit details on any pattern below, see references/ATTACK-PATTERNS.md.
Step 1: Run the Automated Audit
Run from the repository root:
bash <skill-path>/scripts/audit-workflows.sh .github/workflows
Review [CRIT] findings first (exploitable now), then [WARN] (defense gaps).
Step 2: Fix pull_request_target + Fork Checkout (CRITICAL)
This is the #1 attack vector. 4 of 7 hackerbot-claw attacks exploited it. Check every pull_request_target workflow:
# DANGEROUS — runs fork code with your secrets
on: pull_request_target
steps:
- uses: actions/checkout@v4
with:
ref: ${{ github.event.pull_request.head.sha }} # ATTACKER'S CODE
# SAFE — use pull_request trigger instead (no secret access)
on: pull_request
# SAFE — if pull_request_target needed, checkout base only
on: pull_request_target
steps:
- uses: actions/checkout@v4 # defaults to base branch
If the workflow needs both secrets AND fork code (e.g., comment on PR), split into two workflows: one that runs untrusted code (no secrets) and one that consumes artifacts (with secrets).
Step 3: Eliminate Expression Injection in run: Blocks
Any ${{ }} expression referencing user-controlled values inside a run: block is a shell injection. Branch names, filenames, PR titles, commit messages are all vectors.
# VULNERABLE — branch name is shell-evaluated
- run: echo "${{ github.event.pull_request.head.ref }}"
# SAFE — environment variable (properly quoted by runner)
- run: echo "$PR_HEAD_REF"
env:
PR_HEAD_REF: ${{ github.event.pull_request.head.ref }}
What ships with it
2 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.
- 1mo ago First seen · 179 lines · 108 tokens per session scan A e9dd71e254f1
ci-agent-hardening is a skill published in the GitHub repository stacklok/toolhive-catalog (23 stars, last pushed today), licensed Apache-2.0. It adds 108 tokens to every session and 1,775 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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