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AF gmgn-base-tracker

Track tokens on Base chain via GMGN.AI. Covers Trenches (Almost Bonded & Migrated), Trending (1h), Discover (Smart Money, KOL, LIVE, Fresh Wallet, Sniper), and Monitor (Track Smart & KOL 1h). Use when users want to find trending tokens, discover new launches, follow smart money, or monitor KOL activity on Base chain.

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 2 575 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Track tokens on Base chain via GMGN.AI. Covers Trenches (Almost Bonded & Migrated), Trending (1h), Discover (Smart Money, KOL, LIVE, Fresh Wallet, Sniper)…

As a process F 44/100 · Will not run — References files that are not bundled: url, …

ProcedureData 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
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
F
44/100
Will not run
References files that are not bundled: url, …
Tools and files w 18
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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

  • warning missing-ref reference to a missing file: url
  • warning missing-ref reference to a missing file: …

Process rating: all ten parameters 44/100

Will not run. References files that are not bundled: url, …
  • 0Tools and files. 2 referenced file(s) missing: url, …
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 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 (gmgn-base-tracker) differs from the folder (tracking)
  • 60Result and completion. Output format stated, no completion criterion
  • 85Steps. 75 steps, 1 vague phrases
  • 100Failures and branches. 1 branches, has a failure section
  • 100Execution cost. Instruction body is 2575 tokens
  • 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)
  • -212 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 318: enough signal without eating the budget
  • +4Structure: 25 headings
  • +3Step-by-step instructions: 75 items
  • +3Output format is stated explicitly
  • +4Has examples (4 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.