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 autohandai/community-skills --skill agent-toolsgit clone --depth 1 https://github.com/autohandai/community-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/autohandai/community-skills/agent-tools)<a href="https://agentmods.dev/skills/autohandai/community-skills/agent-tools"><img src="https://agentmods.dev/badge/skills/autohandai/community-skills/agent-tools/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/autohandai/community-skills/agent-tools"><img src="https://agentmods.dev/badge/skills/autohandai/community-skills/agent-tools.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 | $0.00141 | $0.01552 |
| Opus 5.5 | $0.00056 | $0.00621 |
| Sonnet 5.5 | $0.00028 | $0.00310 |
| Haiku 4.5 | $0.00014 | $0.00155 |
Grade C, and why
agent-tools scanned grade C with 2 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.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -fsSL https://cli.inference.sh | sh Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -fsSL https://cli.inference.sh | sh How it starts
The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
inference.sh
Run 150+ AI apps in the cloud with a simple CLI. No GPU required.

Install CLI
curl -fsSL https://cli.inference.sh | sh
infsh login
What does the installer do? The install script detects your OS and architecture, downloads the correct binary from
dist.inference.sh, verifies its SHA-256 checksum, and places it in your PATH. That's it — no elevated permissions, no background processes, no telemetry. If you have cosign installed, the installer also verifies the Sigstore signature automatically.Manual install (if you prefer not to pipe to sh):
# Download the binary and checksums curl -LO https://dist.inference.sh/cli/checksums.txt curl -LO $(curl -fsSL https://dist.inference.sh/cli/manifest.json | grep -o '"url":"[^"]*"' | grep $(uname -s | tr A-Z a-z)-$(uname -m | sed 's/x86_64/amd64/;s/aarch64/arm64/') | head -1 | cut -d'"' -f4) # Verify checksum sha256sum -c checksums.txt --ignore-missing # Extract and install tar -xzf inferencesh-cli-*.tar.gz mv inferencesh-cli-* ~/.local/bin/inferencesh
Quick Examples
# Generate an image
infsh app run falai/flux-dev-lora --input '{"prompt": "a cat astronaut"}'
# Generate a video
infsh app run google/veo-3-1-fast --input '{"prompt": "drone over mountains"}'
# Call Claude
infsh app run openrouter/claude-sonnet-45 --input '{"prompt": "Explain quantum computing"}'
# Web search
infsh app run tavily/search-assistant --input '{"query": "latest AI news"}'
# Post to Twitter
infsh app run x/post-tweet --input '{"text": "Hello from AI!"}'
# Generate 3D model
infsh app run infsh/rodin-3d-generator --input '{"prompt": "a wooden chair"}'
Commands
| Task | Command |
|---|---|
| List all apps | infsh app list |
| Search apps | infsh app list --search "flux" |
| Filter by category | infsh app list --category image |
| Get app details | infsh app get google/veo-3-1-fast |
| Generate sample input | infsh app sample google/veo-3-1-fast --save input.json |
| Run app | infsh app run google/veo-3-1-fast --input input.json |
| Run without waiting | infsh app run <app> --input input.json --no-wait |
| Check task status | infsh task get <task-id> |
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 · 127 lines · 141 tokens per session scan C f4877111a8d3
agent-tools is a skill published in the GitHub repository autohandai/community-skills (11 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 141 tokens to every session and 1,552 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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