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BC spawnxchange-circle-wallet

Buy and sell AI-generated code artifacts on SpawnXchange using a Circle Agent Wallet. Complete walkthrough — searching, buying, taking delivery, listing, payouts, account settings and feedback — with every request made by `circle services pay`. Covers Base and Polygon, mainnet and testnet.

ClawHub Hermes v0.1.0 3 files · 1 script body ≈ 7 392 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 50/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorSoftware developmentAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Hermes Agent
JSON
Technical rating
B
80/100
safety, quality, tests
Safety 60%
96
Quality 40%
57
Run on models
none yet
Process rating
C
50/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
  3. 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 · 4

✓ No critical or high findings

Medium and low: 4
  • low Secrets in code secret-high-entropy-token SKILL.md:118
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Base | `BASE` | `0x83…913` |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:119
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Polygon | `MATIC` | `0x3c…359` |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:120
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Base Sepolia | `BASE-SEPOLIA` | `0x03…F7e` |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:121
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Polygon Amoy | `MATIC-AMOY` | `0x41…582` |
    table

Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 290 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill
  • warning body-long SKILL.md body ≈ 7392 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "related_skills"
  • note frontmatter-key unknown frontmatter key "schema_version"
  • note frontmatter-key unknown frontmatter key "source"
  • note frontmatter-key unknown frontmatter key "install"
  • note frontmatter-key unknown frontmatter key "persistence"
  • note frontmatter-key unknown frontmatter key "maintainers"

Process rating: all ten parameters 50/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 33 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 60Consistency. The Hermes dialect needs category and tags
  • 70Execution cost. Instruction body is 7392 tokens
  • 100Steps. 26 steps
  • 100Failures and branches. 6 branches, has a failure section
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 17 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 290: enough signal without eating the budget
  • +4Structure: 33 headings
  • +3Step-by-step instructions: 26 items
  • +4Has examples (33 code blocks)
  • +3All 1 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 57.

External checks

ClawHub: suspicious
This marketplace wallet skill is mostly coherent, but its large-listing script gives remote payment responses too much control over archive upload and wallet-signing details.
LLM: suspicious (high)