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BC aport-agent-guardrail

Pre-action authorization for AI agents. Enforces policies before tools execute—blocks unauthorized commands, data exfiltration, and malicious actions. Works with OpenClaw, IronClaw, PicoClaw via before_tool_call hook. Deterministic enforcement the agent cannot bypass. Optional API mode (APORT_API_URL, APORT_AGENT_ID, APORT_API_KEY) for hosted passports and signed decisions.

Not recommendedcritical or high security findings
modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 3 346 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Pre-action authorization for AI agents.

As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

IntegrationGitHubWhatsAppAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
76/100
safety, quality, tests
Safety 60%
81
Quality 40%
69
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. 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 · 2

  • high Dangerous commands cmd-destructive-fs SKILL.md:113
    Destructive filesystem command (wipes root/home/drive) (documentation of a security skill)
    agent> run rm -rf /
    security skill
Medium and low: 1

✓ Guard found no suspicious behaviour. 1 matches are attack strings quoted in this security skill's own documentation.

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 52/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 10 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 55Failures and branches. 1 branches
  • 60Tools and files. Uses tools (bash, web, git, python, node) that frontmatter does not declare
  • 85Steps. 115 steps, 2 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3346 tokens
  • 100Progress reporting. Reports progress
  • low 14 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)
  • +3Output format is not stated: the model decides each time
  • -232 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 376: enough signal without eating the budget
  • +4Structure: 26 headings
  • +3Step-by-step instructions: 115 items
  • +4Has examples (8 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.