SKILLEMALL.ai
GitHub ↗ RU Sign in

AD aria2-json-rpc

Interact with aria2 download manager via JSON-RPC 2.0. Manage downloads, query status, and control tasks through natural language commands. Use when working with aria2, download management, or torrent operations.

modbender/skill-library-mcp Agent Skills author: modbender MIT 17 files body ≈ 2 372 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Interact with aria2 download manager via JSON-RPC 2.0. Manage downloads, query status, and control tasks through natural language commands. Use when working…

As a process D 49/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, progress reporting

IntegrationAI 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
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
D
49/100
Unfinished process
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: 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 49/100

    • 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
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 60Steps. 77 steps, 6 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2372 tokens
    • 100Running it twice. Mutating operations check current state
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low The response is described with custom markup (3 tags): a typed call is more reliable

    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
    • -33 of 5 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 212: enough signal without eating the budget
    • +4Structure: 20 headings
    • +3Step-by-step instructions: 77 items
    • +4Has examples (12 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.