SKILLEMALL.ai

AC agent-stack-audit

Monthly health check for your agent stack — hunts for zombie crons, dead scripts, unused API keys, superseded tools, and stale subscriptions. Classifies each finding as delete/replace/upgrade/healthy and outputs a ranked cleanup brief for your review. Use when your automation stack feels bloated, when bills are creeping up from unused services, or as a monthly maintenance run to prevent entropy. Prevents "automation debt" — the slow accumulation of dead weight that degrades system reliability.

ClawHub Hermes author: pingukim225 v1.0.0 MIT-0 2 files body ≈ 1 452 tokens Open the sourceclawhub.ai analyzed 3 d ago

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

AnalyzerAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
80
Run on models
none yet
Process rating
C
54/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: ClawHub

How to improve

  1. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 499 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • note frontmatter-key unknown frontmatter key "emoji"

Process rating: all ten parameters 54/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 5 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 100Steps. 34 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1452 tokens
  • 100Progress reporting. Reports progress
  • high The skill tells the model to perform an irreversible action with no human approval

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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 498: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 34 items
  • +3Output format is stated explicitly
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

External checks

ClawHub: suspicious
This is a legitimate audit skill, but it asks to inspect sensitive local/account data and permits some script changes without clear enough user-controlled boundaries.
LLM: suspicious (high) · VirusTotal: · 29 May 2026