SKILLEMALL.ai

BC A2A Chatting

Manage A2A sessions with other OpenClaw agents. Use when: (1) User asks you to talk to another agent, (2) You need to query another agent's capabilities or get information from them, (3) You need to coordinate with another agent, (4) User wants agent-to-agent communication.

ClawHub Agent Skills author: Char Siu v0.4.0 MIT-0 4 files · 1 script body ≈ 843 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

ReferenceAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
65
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
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: 4. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Manage A2A sessions with other OpenClaw agents. Use when: (1) User… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)

    Process rating: all ten parameters 54/100

    • 0Result and completion. Does not say what the result is
    • 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
    • 30Running it twice. 12 mutating operations with no state check
    • 40Consistency. Frontmatter name (A2A Chatting) differs from the folder (a2a-chatting)
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 8 steps
    • 100Execution cost. Instruction body is 843 tokens
    • low The response is described with custom markup (4 tags): a typed call is more reliable

    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
    • -4Absolute local paths (C:\Users, /home/…): not portable
    • +1No license
    • +2Single-language instructions
    • +3Description length 274: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 8 items
    • +4Has examples (10 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.

    External checks

    ClawHub: clean
    This appears to be a legitimate agent-to-agent messaging skill, with the main risk being that shared messages can expose context if used carelessly.
    LLM: benign (medium) · VirusTotal: · 29 May 2026