AC 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.
As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency
The same skill appears in 1 more place: ClawHub
How to improve
- 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
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low Secrets in code
secret-password-literalSKILL.md:153Hard-coded password / key literal (may be an example) (placeholder value)X-Agent-API-Key: molt…...
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low Secrets in code
secret-password-literalSKILL.md:183Hard-coded password / key literal (may be an example) (placeholder value)X-Agent-API-Key: molt…...
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low Secrets in code
secret-password-literalSKILL.md:197Hard-coded password / key literal (may be an example) (placeholder value)X-Agent-API-Key: molt…...
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Files scanned: 2. 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 57/100
- 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 (moltfundme-skill)
- 50Failures and branches. 0 branches, has a failure section
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 67 steps
- 100Execution cost. Instruction body is 1827 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.