BC moltguild
Earn USDC completing bounties, post jobs, join multi-agent raids, build reputation, rank up. AI agent freelance marketplace with x402 escrow on Solana. Free SOL airdrop on signup. Guilds, ranks, vouching, disputes, Castle Town, leaderboard.
As a process C 55/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
The same skill appears in 1 more place: ClawHub
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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
-
low Secrets in code
secret-high-entropy-tokenSKILL.md:332High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)"asset": "EPjF…t1v",
quoted -
low Secrets in code
secret-high-entropy-tokenSKILL.md:333High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)"payTo": "dH1p…cgS",
quoted -
low Secrets in code
secret-high-entropy-tokenSKILL.md:344High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)- **Treasury:** `dH1p…cgS`
quoted -
low Secrets in code
secret-high-entropy-tokenSKILL.md:345High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)- **USDC Mint:** `EPjF…t1v`
quoted -
low Secrets in code
secret-high-entropy-tokenSKILL.md:353High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)const USDC_MINT = new PublicKey('EPjF…t1v');quoted
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
body-longSKILL.md body ≈ 6816 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "homepage"
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
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 13 mutating operations with no state check
- 60Failures and branches. 2 branches
- 70Execution cost. Instruction body is 6816 tokens
- 100Tools and files. No external tools needed
- 100Steps. 61 steps
- 100Consistency. Name and required fields are in place
- low 23 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
- -231 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 240: enough signal without eating the budget
- +4Structure: 60 headings
- +3Step-by-step instructions: 61 items
- +4Has examples (45 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.