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AC agent-tools

Discover agent-callable resources via the agent-tools.cloud directory — x402 paid services (pay-per-call USDC on Base), MCP servers (tools/context), and A2A agents (task delegation). Use when the user wants to find an on-demand paid API, an MCP tool server, or a peer agent to hand a task to. Tools - `search(intent)` finds x402 paid services, `search_mcp_servers(intent)` finds MCP servers, `search_agents(intent)` finds A2A agents, `search_all(intent)` searches all three at once, and the matching `get*(slug)` returns the full call template.

ClawHub Agent Skills author: PikaPikachu v0.1.2 MIT-0 2 files body ≈ 1 236 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

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

IntegrationAI and agentstype 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
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
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

    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 · 0

    ✓ No critical or high findings

    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 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. 2 mutating operations with no state check
    • 40Consistency. Frontmatter name (agent-tools) differs from the folder (agent-tools-cloud)
    • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
    • 60Failures and branches. 2 branches
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 19 steps
    • 100Execution cost. Instruction body is 1236 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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
    • +1No license
    • +2Single-language instructions
    • +3Description length 544: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 19 items
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    This skill is a disclosed directory/search helper for agent tools and paid x402 services, with no artifact evidence of hidden execution or automatic payments.
    LLM: benign (high) · VirusTotal: · 4 Jun 2026