SKILLEMALL.ai

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Agent teams that run growth experiments and build their own playbook. GROWS loop: generate hypothesis, run experiment, observe signal, weigh verdict, stack playbook. 18 pre-built squads covering the full AARRR funnel. Your agents stop guessing and start learning.

Not recommendedcritical or high security findings
ClawHub Hermes author: glitch-rabin v1.0.0 MIT-0 2 files body ≈ 4 131 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 63/100 · Has gaps — weak spots: result and completion, inputs and preconditions

GeneratorAI and agentsInfrastructureMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
82/100
safety, quality, tests
Safety 60%
82
Quality 40%
81
Run on models
none yet
Process rating
C
63/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Tools and files w 18
60
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.

Broad scope
If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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. 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 · 1

  • high Broad scope meta-requests-env-secret SKILL.md:1
    Skill asks the runtime to inject credential env vars into its sandbox: OPENROUTER_API_KEY (high-value: OPENROUTER_API_KEY) — verify each one is needed for the stated purpose
    required_environment_variables: OPENROUTER_API_KEY

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 263 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)

Process rating: all ten parameters 63/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 60Consistency. The Hermes dialect needs category and tags
  • 70Execution cost. Instruction body is 4131 tokens
  • 100Steps. 25 steps
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 1 branches, has a failure section
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • low 12 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
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 263: enough signal without eating the budget
  • +4Structure: 36 headings
  • +3Step-by-step instructions: 25 items
  • +4Has examples (28 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: clean
This is a disclosed growth-experiment helper skill; its main risk is careful handling of the required OpenRouter API key and the external CLI it installs.
LLM: benign (medium) · VirusTotal: · 29 May 2026