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AB bittensor-sdk

Comprehensive Bittensor blockchain interaction skill with wallet management, staking, subnet operations, neuron registration, and emissions tracking. Use for: bittensor operations, subtensor queries, stake/unstake TAO, register neurons, query subnet info, wallet operations, metagraph analysis, emissions tracking, and weight management.

modbender/skill-library-mcp Agent Skills author: modbender MIT 2 files body ≈ 2 235 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Comprehensive Bittensor blockchain interaction skill with wallet management, staking, subnet operations, neuron registration, and emissions tracking.

As a process B 67/100 · Nearly there — weak spots: when it triggers, running it twice

IntegrationWriting and documentstype 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
95/100
safety, quality, tests
Safety 60%
98
Quality 40%
91
Run on models
none yet
Process rating
B
67/100
Nearly there
When it triggers w 12
20
Running it twice w 4
30
Failures and branches w 10
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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Secrets in code secret-high-entropy-token references/API_REFERENCE.md:767
      High-entropy token-like string (may be an id, hash or a credential)
      (5C4h…nhM) for unused hotkeys. This method returns True if the Owner value is anything other than this default.
    • low Secrets in code secret-high-entropy-token references/API_REFERENCE.md:1011
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      # sample return value { "5Grw…tQY": ( (12, "Alice me "5FHn…4ty": ( (12, "Bob mess }
      quoted

    Files scanned: 2. 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 67/100

    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 46 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2235 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 11 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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 337: enough signal without eating the budget
    • +4Structure: 30 headings
    • +3Step-by-step instructions: 46 items
    • +3Output format is stated explicitly
    • +4Has examples (15 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

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