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BB ollama-skill

Use when user wants to integrate Ollama into coding agents, IDEs, or agent harnesses. Supports local/on-prem/Docker deployment, Ollama Cloud, OpenAI/Anthropic-compatible endpoints, streaming, structured outputs, embeddings, tool calling, and web search.

ClawHub Agent Skills author: WaiYanNyeinNaing v1.0.0 MIT-0 17 files · 11 scripts body ≈ 3 827 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

Supports local/on-prem/Docker deployment, Ollama Cloud, OpenAI/Anthropic-compatible endpoints, streaming, structured outputs, embeddings, tool calling, and…

As a process B 68/100 · Nearly there — weak spots: inputs and preconditions, running it twice

IntegrationDockerGitHubAI 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
Technical rating
B
93/100
safety, quality, tests
Safety 60%
99
Quality 40%
85
Run on models
none yet
Process rating
B
68/100
Nearly there
Inputs and preconditions w 11
0
Running it twice w 4
30
When it triggers w 12
50
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Exfiltration read-dotenv SKILL.md:127
      Reads a .env file
      cp .env.example .env

    Files scanned: 17. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 68/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 9 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 100Steps. 113 steps
    • 100Result and completion. Output format and completion criterion are stated
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3827 tokens
    • 100Progress reporting. Reports progress
    • low 15 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)
    • -2localhost URLs: will not work for another user
    • +1No license
    • +2Single-language instructions
    • +3Description length 253: enough signal without eating the budget
    • +4Structure: 38 headings
    • +3Step-by-step instructions: 113 items
    • +3Output format is stated explicitly
    • +4Has examples (12 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: suspicious
    This Ollama integration skill is mostly coherent, but its default Docker examples can expose an unauthenticated Ollama API beyond the local machine and its cloud examples need clearer privacy warnings.
    LLM: suspicious (medium) · VirusTotal: · 16 Sept 2026