SKILLEMALL.ai

BC aws-ses

Amazon SES: sandbox -> production, domain/DKIM/SPF, SMTP creds, Sendy.

ClawHub Hermes author: Abebe v0.1.1 MIT-0 15 files body ≈ 9 424 tokens Open the sourceclawhub.ai analyzed 4 d ago

Amazon SES: sandbox -> production, domain/DKIM/SPF, SMTP creds, Sendy.

As a process C 64/100 · Has gaps — weak spots: consistency, execution cost

ProcedureAWSInfrastructureCustomer supporttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
83/100
safety, quality, tests
Safety 60%
99
Quality 40%
58
Run on models
none yet
Process rating
C
64/100
Has gaps
Consistency w 8
0
Execution cost w 6
40
Failures and branches w 10
50
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
  3. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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

✓ No critical or high findings

Medium and low: 1

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

Files scanned: 13. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 70 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill
  • warning body-long SKILL.md body ≈ 9424 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "author_x"
  • note frontmatter-key unknown frontmatter key "dependencies"

Process rating: all ten parameters 64/100

  • 0Consistency. Frontmatter name (aws-ses) differs from the folder (aws-ses-skill)
  • 40Execution cost. Instruction body is 9424 tokens: crowds the task out of the window
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 119 steps
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 16 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 70: 120–800 characters recommended
  • +2Single-language instructions
  • +4Structure: 64 headings
  • +3Step-by-step instructions: 119 items
  • +3Output format is stated explicitly
  • +4Has examples (33 code blocks)
  • +3All 6 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 58.

External checks

ClawHub: clean
This is a coherent AWS SES setup skill with expected AWS account access and email-sending utilities, but users should handle generated SMTP credentials carefully.
LLM: benign (high) · VirusTotal: · 19 Aug 2026