AC agent-zero-bridge
Delegate complex coding, research, or autonomous tasks to Agent Zero framework. Use when user says "ask Agent Zero", "delegate to A0", "have Agent Zero build", or needs long-running autonomous coding with self-correction loops. Supports bidirectional communication, file attachments, task breakdown, and progress reporting.
As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".
If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.
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 · 5
✓ No critical or high findings
Medium and low: 5
-
medium Exfiltration
net-redirectable-api-keyscripts/lib/config.js:28Helper sends the API key to a host configured by an environment variable — the key can be redirected to another serverAPI key + configurable base URL from environment
-
low Exfiltration
read-dotenvREADME.md:39Reads a .env filecp .env.example .env
-
low Exfiltration
read-dotenvSKILL.md:32Reads a .env filecp .env.example .env
-
low Secrets in code
secret-high-entropy-tokenSKILL.md:53High-entropy token-like string (may be an id, hash or a credential) (placeholder value)runtime_id = "your…_ID" # from A0's .env
placeholder -
low Exfiltration
read-dotenvSKILL.md:77Reads a .env filedocker cp .env <container>:/a0/bridge/
Files scanned: 10. 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 56/100
- 0Result and completion. Does not say what the result is
- 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
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 8 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 849 tokens
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -2localhost URLs: will not work for another user
- +1No license
- +2Single-language instructions
- +5Description quotes 3 example trigger phrases
- +3Description length 323: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 8 items
- +4Has examples (9 code blocks)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.