SKILLEMALL.ai

CD a2ap

A2AP — AI Agent互联互通的第一开放协议。6个LIVE能力(humanize_text/memory_evolve/skill_audit/news_briefing/agent_peering/custom_agent_dev)全部通过DeepSeek V4 Pro真机实现。公网已打通 frp-can.com:51831,支持HTTP Bridge & MCP桥接(87K⭐生态直接调用)。Hermes↔OpenClaw双向通知桥。TCP原始协议(非HTTP),默认端口9800。CC BY-SA 4.0。

ClawHub Agent Skills author: thebuddha5566 v1.5.0 MIT-0 2 files body ≈ 0 tokens Open the sourceclawhub.ai analyzed 32 h ago

A2AP — AI Agent互联互通的第一开放协议。6个LIVE能力(humanizetext/memoryevolve/skillaudit/newsbriefing/agentpeering/customagentdev)全部通过DeepSeek V4 Pro真机实现。公网已打通…

As a process D 38/100 · Unfinished process — weak spots: steps, result and completion, when it triggers

ReferenceAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
62/100
safety, quality, tests
Safety 60%
100
Quality 40%
6
Run on models
none yet
Process rating
D
38/100
Unfinished process
Steps w 15
0
Result and completion w 14
0
Inputs and preconditions w 11
0
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.
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

  • error body-empty SKILL.md: empty instructions body
  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 38/100

  • 0Steps. Prose only: no discrete steps
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 100Tools and files. No external tools needed
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 0 tokens
  • 100Running it twice. No mutating operations

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)
  • +4Structure: 0 headings, hard to scan
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • -15SKILL.md body under 300 characters: nearly empty
  • +1No license
  • +2Single-language instructions
  • +3Description length 261: enough signal without eating the budget

Quality base 70; lint remarks subtract, signals add up to 100. Result: 6.

External checks

ClawHub: clean
The submitted skill artifact is only descriptive metadata and shows no install-time code, hidden execution, persistence, or data access.
LLM: benign (medium) · VirusTotal: · 8 Jun 2026