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BD trends-coin-create

在 trends.fun 上创建 coin 并部署 Meteora DBC 资金池

modbender/skill-library-mcp Agent Skills author: modbender MIT 10 files body ≈ 548 tokens Open the sourcegithub.com↗ analyzed 2 d ago

在 trends.fun 上创建 coin 并部署 Meteora DBC 资金池

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

Generatortype 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
79/100
safety, quality, tests
Safety 60%
86
Quality 40%
69
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 14

✓ No critical or high findings

Medium and low: 14
  • low Secrets in code secret-high-entropy-token package-lock.json:64
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…rAV+/W2RQ…lxf+8fKkmSfQ==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:82
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…kJw+JUEz…Ry8+JzNy…KLw==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:107
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…7pY+zoMV…h0x/Ptw8…8dg==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:124
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…b00+Gxjx…zRc/oZwU…hzA==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:192
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha512-vHk/hA7/1Ack…wbo+jaSh…Gtl+A5zq…HFg==",
    detector
  • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:56
    High-entropy token-like string (may be an id, hash or a credential)
    resolution: {integrity: sha5…rAV+/W2RQ…lxf+8fKkmSfQ==}
  • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:60
    High-entropy token-like string (may be an id, hash or a credential)
    resolution: {integrity: sha5…m48+9Ovm…EqH/ti/7ASj…sop+LQ==}
  • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:84
    High-entropy token-like string (may be an id, hash or a credential)
    resolution: {integrity: sha5…7pY+zoMV…h0x/Ptw8…8dg==}
  • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:96
    High-entropy token-like string (may be an id, hash or a credential)
    resolution: {integrity: sha5…b00+Gxjx…zRc/oZwU…hzA==}
  • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:114
    High-entropy token-like string (may be an id, hash or a credential)
    resolution: {integrity: sha512-vHk/hA7/1Ack…wbo+jaSh…Gtl+A5zq…HFg==}
  • low Secrets in code secret-high-entropy-token SKILL.md:48
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | `TRENDS_POOL_CONFIG` | ❌ | `7UQp…9AA` | Trends.fun 使用的 pool_config 地址 |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:103
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - pool_config 默认使用 trends.fun 的配置: `7UQp…9AA`，可通过环境变量 `TRENDS_POOL_CONFIG` 自定义
    quoted
  • low Secrets in code secret-high-entropy-token src/index.ts:14
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    const DEFAULT_POOL_CONFIG = "7UQp…9AA";
    quoted
  • low Secrets in code secret-high-entropy-token src/pool.ts:13
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    const DEFAULT_POOL_CONFIG = "7UQp…9AA";
    quoted

Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 46/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 2 mutating operations with no state check
  • 40Consistency. Frontmatter name (trends-coin-create) differs from the folder (trendsdotfun)
  • 100Tools and files. No external tools needed
  • 100Steps. 16 steps
  • 100Execution cost. Instruction body is 548 tokens

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 41: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 16 items
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.