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BC moltfundme

Browse and advocate for crowdfunding campaigns on MoltFundMe. Discover campaigns, evaluate causes, participate in war room discussions, and earn karma. Use when the user mentions MoltFundMe, crowdfunding, crypto donations, or campaign advocacy.

modbender/skill-library-mcp Agent Skills author: modbender MIT 80 files body ≈ 1 882 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Browse and advocate for crowdfunding campaigns on MoltFundMe.

As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

AnalyzerMarketingtype 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%
91
Quality 40%
82
Run on models
none yet
Process rating
C
55/100
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
This is a copy of a skill from another catalog; the rating counts the canonical one: moltfundme (modbender/skill-library-mcp)

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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
    • medium Broad scope meta-agent-memory-dump agents/doc/memory.md
      Agent memory / workspace files bundled with the skill (10) — likely a workspace dump with personal data or tokens
      agents/doc/memory.md, agents/doc/soul.md, agents/flick/memory.md, agents/flick/soul.md, agents/mira/memory.md
    • low Secrets in code secret-high-entropy-token api/app/services/blockchain.py:8
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      USDC_BASE_CONTRACT = "0x83…913"
      quoted
    • low Secrets in code secret-password-literal SKILL.md:153
      Hard-coded password / key literal (may be an example) (placeholder value)
      X-Agent-API-Key: molt…...
      placeholder
    • low Secrets in code secret-password-literal SKILL.md:183
      Hard-coded password / key literal (may be an example) (placeholder value)
      X-Agent-API-Key: molt…...
      placeholder
    • low Secrets in code secret-password-literal SKILL.md:197
      Hard-coded password / key literal (may be an example) (placeholder value)
      X-Agent-API-Key: molt…...
      placeholder

    Files scanned: 80. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 55/100

    • 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. 6 mutating operations with no state check
    • 40Consistency. Frontmatter name (moltfundme) differs from the folder (molt)
    • 50Failures and branches. 0 branches, has a failure section
    • 70When it triggers. States when to use, but not when not to
    • 85Steps. 67 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Execution cost. Instruction body is 1882 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)
    • +3Output format is not stated: the model decides each time
    • -2localhost URLs: will not work for another user
    • +1No license
    • +2Single-language instructions
    • +3Description length 244: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 67 items
    • +4Has examples (8 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.