SKILLEMALL.ai

CB linux-forensics

Generalized Linux incident response and forensic analysis covering Debian/Ubuntu, RHEL/CentOS/Rocky, and SUSE families

jmagly/aiwg Agent Skills author: jmagly 1 file body ≈ 1 381 tokens Open the sourcegithub.com↗ analyzed 10 h ago

Generalized Linux incident response and forensic analysis covering Debian/Ubuntu, RHEL/CentOS/Rocky, and SUSE families

As a process B 66/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, running it twice

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
C
87/100
safety, quality, tests
Safety 60%
98
Quality 40%
70
Run on models
none yet
Process rating
B
66/100
Nearly there
Inputs and preconditions w 11
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: linux-forensics (jmagly/aiwg)

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 2

✓ No critical or high findings

Medium and low: 2

✓ Guard found no suspicious behaviour. 2 matches are attack strings quoted in this security skill's own documentation.

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "namespace"
  • note frontmatter-key unknown frontmatter key "tools"

Process rating: all ten parameters 66/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Result and completion. Output format stated, no completion criterion
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 51 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1381 tokens
  • 100Progress reporting. Reports progress
  • low The response is described with custom markup (4 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
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 118: 120–800 characters recommended
  • +1No license
  • +2Single-language instructions
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 51 items
  • +3Output format is stated explicitly
  • +4Has examples (4 code blocks)

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