SKILLEMALL.ai

CF dilbert

(no description)

sundial-org/awesome-openclaw-skills Agent Skills author: sundial-org 4 files · 2 scripts body ≈ 61 tokens Open the sourcegithub.com analyzed 2 d ago

This skill fetches a random Dilbert comic from an archive source and sends it to the chat.

As a process F 26/100 · Will not run — weak spots: steps, result and completion, when it triggers

Referencetype and topics are labelled automatically from the skill text
JSON
Technical rating
C
63/100
safety, quality, tests
Safety 60%
99
Quality 40%
10
Run on models
none yet
Process rating
F
26/100
Will not run
Steps w 15
0
Result and completion w 14
0
When it triggers w 12
0
the three weakest of ten parameters · all ten

How to improve

  1. Add a description to the frontmatter: without it the skill never triggers.
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
  • low Exfiltration exfil-webhook-url daily_dilbert.sh:13
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    curl -s -X POST "https://api.telegram.org/bot<YOUR_BOT_TOKEN>/sendPhoto" \
    placeholder

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error description-missing SKILL.md: no `description` — the skill can never trigger

Process rating: all ten parameters 26/100

  • 0Steps. Prose only: no discrete steps
  • 0Result and completion. Does not say what the result is
  • 0When it triggers. No condition that starts the skill
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 2 mutating operations with no state check
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 61 tokens

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 0: 120–800 characters recommended
  • +4Structure: 1 headings, hard to scan
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • -15SKILL.md body under 300 characters: nearly empty
  • +1No license
  • +2Single-language instructions

Quality base 70; lint remarks subtract, signals add up to 100. Result: 10.