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AC octoflow

Use when the user wants to run GPU-accelerated computations, analyze data, process images, train ML models, or generate code from natural language. OctoFlow turns English task descriptions into GPU programs via Vulkan. Also runs as an MCP server (`octoflow mcp-serve`) with 7 structured tools. No Python, no CUDA, no dependencies — single 3.2 MB binary. Use for: "sort a million numbers", "cluster this CSV", "blur this image", "plot my data", "calculate statistics", "run regression".

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 1 408 tokens Open the sourcegithub.com↗ analyzed 3 d ago

OctoFlow turns English task descriptions into GPU programs via Vulkan.

As a process C 58/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

AnalyzerGitHubData and analyticstype 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
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
91
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
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 · 0

    ✓ No critical or high findings

    Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "display_name"
    • note frontmatter-key unknown frontmatter key "repository"
    • note frontmatter-key unknown frontmatter key "homepage"
    • note frontmatter-key unknown frontmatter key "permissions"

    Process rating: all ten parameters 58/100

    • 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
    • 30Running it twice. 1 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 100Steps. 19 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1408 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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

    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +5Description quotes 6 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 485: enough signal without eating the budget
    • +4Structure: 20 headings
    • +3Step-by-step instructions: 19 items
    • +4Has examples (10 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.