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A python-sdk

Python SDK for inference.sh - run AI apps, build agents, and integrate with 150+ models. Package: inferencesh (pip install inferencesh). Supports sync/async, streaming, file uploads. Build agents with template or ad-hoc patterns, tool builder API, skills, and human approval. Use for: Python integration, AI apps, agent development, RAG pipelines, automation. Triggers: python sdk, inferencesh, pip install, python api, python client, async inference, python agent, tool builder python, programmatic ai, python integration, sdk python

ClawHub Agent Skills author: Ömer Karışman v0.1.5 8 files body ≈ 2 644 tokens open source ↗ analyzed 30 h ago
IntegrationSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
A
93/100
Overall score
Safety 60%
97
Quality 40%
88
Tests bonus
0

How to improve

  1. Add evals/evals.json with 4–6 real requests and expected answers: the full check will then use your cases instead of a model draft.
  2. Add a spec.yaml with triggers and assertions (skilltest init): the behaviour contract for CI.

Guard findings · 3

✓ No critical or high findings

Medium and low: 3
  • low Exfiltration exfil-webhook-url references/tool-builder.md:172
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    webhook_tool("notify_slack", "https://hooks.slack.com/services/...")
    placeholder
  • low Exfiltration exfil-webhook-url references/tool-builder.md:338
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    webhook_tool("notify", "https://hooks.slack.com/...")
    placeholder
  • low Exfiltration exfil-webhook-url SKILL.md:302
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    webhook_tool("slack", "https://hooks.slack.com/...")
    placeholder

Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

Lint

✓ Lint: no remarks

Process maturity 56/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 2 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 12 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2644 tokens
  • low 17 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 534: enough signal without eating the budget
  • +4Structure: 33 headings
  • +3Step-by-step instructions: 12 items
  • +4Has examples (25 code blocks)
  • +4Reference files are cited in the instructions (6 of 6)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

External checks

ClawHub: suspicious
This appears to be a real inference.sh Python SDK documentation skill, but some examples could expose files, conversations, or local code execution if copied without extra safeguards.
LLM: suspicious (high) · VirusTotal: suspicious · 10 Sept 2026