CB agent-agent
Agent skill for agent - invoke with $agent-agent
This skill lets an AI agent invoke another agent via $agent-agent—basically task delegation within the system. Single instruction file with 6270 tokens, no critical errors, safety score maxed out. Code quality sits at 71%, process score 67%—mid-range marks suggesting either bloat or unclear use cases.
No model runs, no sandbox testing. Platform support is broad: Claude, Cursor, DeepSeek, Mistral, and others covered. Worth installing if you're already running multi-agent setups and need straightforward context passing between agents without extra complexity.
Agent skill for agent - invoke with $agent-agent
As a process B 67/100 · Nearly there — weak spots: result and completion, when it triggers, running it twice
The same skill appears in 1 more place: RA-Skills
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 6270 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 67/100
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 3 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 50Failures and branches. 0 branches, has a failure section
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 6270 tokens
- 100Tools and files. No external tools needed
- 100Steps. 60 steps
- 100Consistency. Name and required fields are in place
- low 10 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)
- +3Description length 48: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 45 headings
- +3Step-by-step instructions: 60 items
- +4Has examples (21 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.