AB create-agent-with-telegram-group
Create a new OpenClaw agent and bind it to a dedicated Telegram group with workspace ~/claw-<agent-name>. Use when the user asks for one-agent-one-group setup, Telegram group binding, or repeatable agent provisioning. Always ask which model to use, ask for essential initialization choices (USER.md/IDENTITY.md/SOUL.md), and set group reply mode to no-mention-required. Explicit user confirmation is required before any high-privilege actions: modifying openclaw.json, triggering browser automation, or restarting the gateway.
As a process B 76/100 · Nearly there — weak spots: progress reporting
How to improve
- 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-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Create a new OpenClaw agent and bind it to a dedicated Telegram gr… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
Process rating: all ten parameters 76/100
- 0Progress reporting. Says nothing while it works
- 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 102 steps, 2 vague phrases
- 100Failures and branches. 15 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1834 tokens
- 100Running it twice. Mutating operations check current state
- low 11 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (9 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)
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 526: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 102 items
- +3Output format is stated explicitly
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.