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BC productclank-campaigns

Community-powered growth for builders. Boost amplifies your social posts with authentic community engagement (replies, likes, reposts). Discover finds relevant conversations and generates AI-powered replies at scale. Use Boost when the user has a post URL. Use Discover when the user wants to find and engage in conversations about their product.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 6 files body ≈ 5 449 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Community-powered growth for builders.

As a process C 51/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

ProcedureAI and agentsMarketingtype 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
87/100
safety, quality, tests
Safety 60%
97
Quality 40%
71
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
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 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 · 3

✓ No critical or high findings

Medium and low: 3
  • low Secrets in code secret-high-entropy-token references/API_REFERENCE.md:912
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - Send exact USDC amount to `0x87…F68` on Base
    quoted
  • low Secrets in code secret-high-entropy-token references/API_REFERENCE.md:1019
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    **Payment Address:** `0x87…F68`
    quoted
  • low Secrets in code secret-high-entropy-token references/API_REFERENCE.md:1020
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    **USDC Contract:** `0x83…913`
    quoted

Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5449 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 51/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 8 mutating operations with no state check
  • 40Consistency. Frontmatter name (productclank-campaigns) differs from the folder (productclank-community-growth)
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 70Execution cost. Instruction body is 5449 tokens
  • 85Steps. 65 steps, 2 vague phrases
  • 100Failures and branches. 2 branches, has a failure section
  • 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)
  • +3Output format is not stated: the model decides each time
  • -5TODO / placeholder text left in the skill
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 346: enough signal without eating the budget
  • +4Structure: 37 headings
  • +3Step-by-step instructions: 65 items
  • +4Has examples (16 code blocks)
  • +4Reference files are cited in the instructions (1 of 2)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.