📦
remotion-render
38Render Remotion Videos from React Code
Teams need repeatable video rendering without managing a local Remotion pipeline. This skill sends React/Remotion components to inference.sh and returns an MP4.
Design & Creative View
Skills agent-tools
📦
agent-tools
Content revision r1 Critical 🌐 Network access🔑 Env variables📁 Filesystem access⚙️ External commands
Run AI Apps from the CLI
Teams need a consistent way to invoke many AI services without custom integrations. This skill guides Claude, Codex, and Claude Code to use the inference.sh CLI for discovery, execution, and task tracking.
Supports: Claude Codex Code(CC)
Do not auto-install this skill.
The canonical policy requires operator review before any installation action.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Agent request
Review the Skillstore skill "agent-tools" from https://skillstore.io/skills/inference-sh-6-agent-tools.md and its manifest at https://skillstore.io/api/skills/inference-sh-6-agent-tools/manifest. Verify the artifact. Do not auto-install. Inspect the skill and report your findings, then wait for an operator or manual installation decision.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "agent-tools". Find apps that can generate short product videos.
Expected outcome:
A ranked list of relevant video apps, key provider names, expected input fields, and a recommended first test.
Using "agent-tools". Run an image generation prompt and track completion.
Expected outcome:
The assistant selects an app, submits the job, reports the task ID, and summarizes the output URL when ready.
Using "agent-tools". Prepare a safe Twitter/X post workflow.
Expected outcome:
The assistant identifies the required X app, asks for confirmation, and explains the account action before running it.
Security Audit
Criticalv4 • 7/5/2026 Open versioned report
The skill is transparent about using the inference.sh CLI, but several install instructions use curl-to-shell and remote binary installation patterns. Most API-key and documentation-link findings are false positives, while external CLI execution, hosted-app data transfer, and Twitter/X automation remain real risks.
5
Files scanned
554
Lines analyzed
22
Review items
0
False positives ignored
Confirmed security concerns (6)
Critical
Pipe to shell pattern
curl -fsSL https://cli.inference.sh | sh
The command pipes a remotely downloaded installer directly into sh. This can execute changed or compromised remote content without local inspection.
Critical
Pipe to shell pattern
curl -fsSL https://cli.inference.sh | sh
The reinstall example repeats the curl-to-shell pattern. It allows remote script content to execute immediately on the user machine.
Critical
Pipe to shell pattern
curl -fsSL https://cli.inference.sh | sh
The installation example pipes a remote script directly to sh. That is a recognized high-risk install pattern even when the domain is expected.
Critical
Pipe to shell pattern
curl -fsSL https://cli.inference.sh | sh
The primary install instruction executes remote shell content with sh. This is a critical supply-chain risk if the endpoint or transport is compromised.
High
Public Social Media Automation Capability
The skill includes examples for x/post-tweet and lists Twitter/X actions such as posting, direct messages, follows, likes, and retweets. These actions can affect a public account when run with authenticated credentials.
The cited lines explicitly show x/post-tweet and Twitter/X automation commands. Misuse depends on credentials, but the business action is clear.
Medium
User Data Sent to Hosted Third-Party Apps
The skill routes prompts and input files to hosted apps such as image, video, LLM, search, and 3D services through infsh app run. This can expose user content to the selected app provider.
The examples show remote app execution with prompts, and the references state that outputs are returned through cloud URLs. The behavior is intended but privacy-relevant.
Capability review items (22)
These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.
High
Shell command substitution
> curl -LO $(curl -fsSL https://dist.inference.sh/cli/manifest.json | grep -o '"url":"[^"]*"' | grep
The command uses nested shell substitution with a remote manifest to build a download URL. A changed manifest can influence what binary is downloaded.
High
Hidden file in home directory
> mv inferencesh-cli-* ~/.local/bin/inferencesh
The manual install command moves a downloaded executable into ~/.local/bin. That is a normal user install path, but it places remote code in PATH.
Medium
Ruby/shell backtick execution
> ```bash
The referenced manual install block contains shell commands that download, verify, extract, and install a remote binary. It is documented setup, but it still executes external commands on the user system.
Medium
Ruby/shell backtick execution
```bash
The quick examples contain infsh app run commands that send prompts to hosted AI apps. This is intended behavior, but it is real external command execution.
Medium
Ruby/shell backtick execution
| List all apps | `infsh app list` |
The command invokes infsh to list remote apps. It is expected read-only behavior, but it still runs an external CLI against a network service.
Medium
Ruby/shell backtick execution
| Search apps | `infsh app list --search "flux"` |
The command invokes infsh search against the hosted app catalog. It is a legitimate command, but it is external CLI activity.
Medium
Ruby/shell backtick execution
| Filter by category | `infsh app list --category image` |
The category filter runs infsh against the remote app catalog. This is intended but still an external command path.
Medium
Ruby/shell backtick execution
| Get app details | `infsh app get google/veo-3-1-fast` |
The command retrieves remote app details through infsh. It is normal discovery behavior, but it depends on external CLI execution.
Medium
Ruby/shell backtick execution
| Generate sample input | `infsh app sample google/veo-3-1-fast --save input.json` |
The command generates and saves a sample input file through infsh. It combines external CLI use with a local file write.
Medium
Ruby/shell backtick execution
| Run app | `infsh app run google/veo-3-1-fast --input input.json` |
The command runs a hosted AI app with local input. It can transmit user-provided data to a remote service.
Medium
Ruby/shell backtick execution
| Run without waiting | `infsh app run <app> --input input.json --no-wait` |
The no-wait run command submits remote work and returns before completion. It can transmit data and leave asynchronous jobs running.
Medium
Ruby/shell backtick execution
| Check task status | `infsh task get <task-id>` |
The task status command calls the remote inference.sh service. It is expected behavior, but it is still external command execution.
Medium
Ruby/shell backtick execution
```bash
The related-skills block uses npx skills add commands to install additional skills. Installing more community capabilities expands the execution surface.
Medium
Template literal with command substitution
> ```bash
The manual install block includes shell substitution and several shell commands. It is legitimate installation guidance, but it raises command execution risk.
Medium
Hidden file access
> mv inferencesh-cli-* ~/.local/bin/inferencesh
The command writes into a hidden home-directory path used for local executables. This is expected installation behavior, but it changes user executable search paths.
Low
Hardcoded URL
curl -fsSL https://cli.inference.sh | sh
The hardcoded URL is used in an installer command that retrieves remote shell content. The network endpoint is expected, but it is security-relevant because it controls the script source.
Low
Hardcoded URL
curl -fsSL https://cli.inference.sh | sh
The reinstall command fetches a remote installer script from a fixed URL. This is expected setup behavior, but it depends on a remote network source.
Low
Hardcoded URL
curl -fsSL https://cli.inference.sh | sh
The hardcoded URL is part of a CLI installation command that fetches remote shell content. This network dependency is expected but security-relevant.
Low
Hardcoded URL
](https://cloud.inference.sh/app/files/u/4mg21r6ta37mpaz6ktzwt
The Markdown image embeds a remote cloud.inference.sh asset. It is not code execution, but rendering the skill can trigger a third-party network request.
Low
Hardcoded URL
curl -fsSL https://cli.inference.sh | sh
The URL is used by the curl-to-shell install command. Fetching installer code from a fixed remote endpoint is security-relevant.
Low
Hardcoded URL
> curl -LO https://dist.inference.sh/cli/checksums.txt
The command downloads checksums from a fixed remote endpoint. This is expected verification flow, but it is still a trusted network dependency.
Low
Hardcoded URL
> curl -LO $(curl -fsSL https://dist.inference.sh/cli/manifest.json | grep -o '"url":"[^"]*"' | grep
The command downloads and parses a remote manifest to select a binary URL. This network-controlled input influences the installation artifact.
Risk Factors
🌐 Network access (17)
🔑 Env variables (3)
📁 Filesystem access (4)
Detected Patterns
Pipe to shell pattern×4
Audited by: codex View Audit History →
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APA citation
inference-sh-6. (2026). agent-tools security audit report (audit version 4) [Author version unspecified]. Skillstore. https://skillstore.io/skills/inference-sh-6-agent-tools/audits/4BibTeX citation
@techreport{inference-sh-6-inference-sh-6-agent-tools-2026,
author = {inference-sh-6},
title = {agent-tools security audit report (audit version 4)},
institution = {Skillstore},
year = {2026},
number = {4},
url = {https://skillstore.io/skills/inference-sh-6-agent-tools/audits/4},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "agent-tools security audit report (audit version 4)"
version: "unspecified"
type: report
authors:
- name: "inference-sh-6"
date-released: "2026-07-05"
url: "https://skillstore.io/skills/inference-sh-6-agent-tools/audits/4"
identifiers:
- type: other
value: "skillstore:inference-sh-6-agent-tools:audit:4"
description: "Skillstore immutable audit report identifier"
Compare variants
20 installable variantsEach author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.
Why this variant is first
Higher Skillstore usage
Author / source Skillstore Score Evidence Confidence Skillstore usage Updated
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Skillstore Score 38
Evidence Confidence Medium
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Skillstore Score 38
Evidence Confidence Medium
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2026-08-21
infsh-skills-agent-tools
Skillstore Score 38
Evidence Confidence Medium
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2026-08-21
inference-sh-6 Current
inference-sh-6-agent-tools
Skillstore Score 38
Evidence Confidence Medium
Skillstore usage 7
Updated
2026-08-21
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Skillstore Score 38
Evidence Confidence Medium
Skillstore usage 7
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inference-shell-agent-tools
Skillstore Score 38
Evidence Confidence Medium
Skillstore usage 6
Updated
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Skillstore Score 38
Evidence Confidence Medium
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Skillstore Score 38
Evidence Confidence Medium
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Evidence Confidence Medium
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Updated
2026-08-21
Skillstore Score
Why this score Evidence Confidence: Medium 45
Architecture
85
Maintainability
87
Content
72
Community
91
Spec Compliance
What You Can Build
Prototype multimodal AI workflows
Find hosted models, generate sample inputs, run jobs, and inspect task results from one CLI workflow.
Create media assets quickly
Run image, video, audio, and 3D generation apps without managing local GPU infrastructure.
Compare hosted model capabilities
Search the app catalog, review provider options, and test LLM, search, and media apps with controlled inputs.
Try These Prompts
Find an app
Use agent-tools to find inference.sh apps for image generation. Show suitable options and explain when to use each one.
Run a simple job
Use agent-tools to run a hosted image app with this prompt: a clean product photo on a white background. Report the task result.
Build a sample-driven workflow
Use agent-tools to get app details, generate a sample input file, explain the key fields, and run the app after I approve the input.
Coordinate a long-running job
Use agent-tools to submit a video generation job without waiting, capture the task ID, check status, and summarize the final output when ready.
Best Practices
- Confirm the app namespace, provider, and expected cost before long jobs.
- Use sample input files for complex apps so parameters are visible before execution.
- Review outputs and credentials before any public posting or account action.
Avoid
- Running installer commands from an untrusted network without verification.
- Sending private data to unknown apps or providers.
- Allowing unattended social media actions from an authenticated account.
Frequently Asked Questions
Do I need an inference.sh account?
Yes. The CLI must be installed and authenticated before most app commands can run.
Can this skill run image and video models?
Yes. It documents image, video, audio, 3D, LLM, search, and utility app categories.
Does it work with Claude, Codex, and Claude Code?
Yes. The marketplace metadata lists Claude, Codex, and Claude Code as supported tools.
Where do results come from?
Results come from hosted inference.sh apps and may include cloud URLs for generated files.
Can it post to Twitter/X?
Yes, when the account is configured. Confirm the exact action before posting, messaging, following, liking, or retweeting.
Is sensitive data safe to send?
Only send data that is appropriate for the selected provider and app. Review app details before submitting private content.
Developer Details
Author
inference-sh-6License
MIT
Skillstore revision
r1
Version notice
The author did not declare a version.
Ref
a25199bc7d6b82598536822d1738eb5d5f54025b
Maintenance freshness
7/18/2026
Usage
6 downloads · 347 views
File structure
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