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AC web3-protocol-gtm

Go-to-market strategy for web3 builders - protocols, products, services, and solo founders. Use when planning growth for a crypto protocol, building developer community, crafting CT narrative, planning ecosystem partnerships, preparing grant applications, launching tokens, pricing crypto-native products, or growing as a solo founder in web3.

ClawHub Agent Skills author: Misha Kolesnik v0.2.6 MIT-0 11 files body ≈ 5 881 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 60/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorInfrastructuretype 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%
98
Quality 40%
79
Run on models
none yet
Process rating
C
60/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 Risky intent intent-offensive-security references/metrics-launch.md:209
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    - [ ] Bug bounty program ($500-$5K range, proportional to TVL risk)
  • low Risky intent intent-offensive-security SKILL.md:381
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    - Bug bounty (even small: $500-$5K range)

Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5881 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 60/100

  • 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. 3 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 60Failures and branches. 2 branches
  • 70Execution cost. Instruction body is 5881 tokens
  • 100Tools and files. No external tools needed
  • 100Steps. 65 steps
  • 100Consistency. Name and required fields are in place
  • low 13 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)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +3Description length 343: enough signal without eating the budget
  • +4Structure: 42 headings
  • +3Step-by-step instructions: 65 items
  • +4Has examples (16 code blocks)
  • +4Reference files are cited in the instructions (8 of 8)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

External checks

ClawHub: suspicious
This is a non-executable web3 GTM guide, but parts of its crypto launch and growth advice are high-risk and not bounded clearly enough.
LLM: suspicious (medium) · 21 Aug 2026