SKILLEMALL.ai

CD atomicmail

Read and write email through the Atomic Mail from an AI agent. Handles proof-of-work authentication and JMAP so the agent thinks in JMAP method calls. Use when the user asks to register an email inbox, list mailboxes, fetch or send email, or schedule meetings by email (calendar invitations).

Not recommendedcritical or high security findings
Atomic-Mail/atomic-mail-agentic Agent Skills author: Atomic-Mail 33 files · 4 scripts body ≈ 2 201 tokens Open the sourcegithub.com↗ analyzed 57 min ago

Read and write email through the Atomic Mail from an AI agent.

As a process D 47/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches

GeneratorPersonal productivityAI and agentsWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
82/100
safety, quality, tests
Safety 60%
82
Quality 40%
81
Run on models
none yet
Process rating
D
47/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: atomicmail (Atomic-Mail/atomic-mail-agentic)

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.

Exfiltration
If you install

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".

For the author

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

  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.
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 Exfiltration exfil-webhook-url webhooks.md:455
    Webhook / callback URL commonly used for exfiltration (verify the destination)
    point an endpoint at a request bin such as [webhook.site](https://webhook.site).

Files scanned: 33. 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 47/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 30Running it twice. 12 mutating operations with no state check
  • 40Consistency. Frontmatter name (atomicmail) differs from the folder (docs)
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 20 steps
  • 100Execution cost. Instruction body is 2201 tokens
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 292: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 20 items
  • +4Has examples (9 code blocks)

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