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BC sablier-vesting

Create and manage token vesting streams using the Sablier Lockup protocol (linear, dynamic, tranched).

modbender/skill-library-mcp Claude Code author: modbender MIT 1 file body ≈ 4 480 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Create and manage token vesting streams using the Sablier Lockup protocol (linear, dynamic, tranched).

As a process C 57/100 · Has gaps — weak spots: result and completion, consistency, running it twice

GeneratorGitHubAI and agentsInfrastructuretype 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
89/100
safety, quality, tests
Safety 60%
95
Quality 40%
80
Run on models
none yet
Process rating
C
57/100
Has gaps
Result and completion w 14
0
Running it twice w 4
30
Consistency w 8
40
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 · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Secrets in code secret-high-entropy-token SKILL.md:115
      High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
      | **Ethereum** | `0xcF…A73` | `0x06…45a` |
      table
    • low Secrets in code secret-high-entropy-token SKILL.md:116
      High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
      | **Arbitrum** | `0xF1…Db5` | `0xf0…d25` |
      table
    • low Secrets in code secret-high-entropy-token SKILL.md:118
      High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
      | **OP Mainnet** | `0xe2…fd0` | `0xf3…6FC` |
      table
    • low Secrets in code secret-high-entropy-token SKILL.md:119
      High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
      | **Polygon** | `0x1E…2EF` | `0x33…845` |
      table
    • low Secrets in code secret-high-entropy-token SKILL.md:120
      High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
      | **BNB Chain** | `0x06…C74` | `0xFE…67f` |
      table

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

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 57/100

    • 0Result and completion. Does not say what the result is
    • 30Running it twice. 33 mutating operations with no state check
    • 40Consistency. Frontmatter name (sablier-vesting) differs from the folder (token-vesting)
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Failures and branches. 4 branches
    • 70Execution cost. Instruction body is 4480 tokens
    • 85Steps. 45 steps, 1 vague phrases
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 10 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)
    • +3Description length 102: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Structure: 31 headings
    • +3Step-by-step instructions: 45 items
    • +4Has examples (22 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.