SKILLEMALL.ai

CF LLM Wiki Maintainer

Use the LLM Wiki plugin tools to maintain a cited local company wiki.

paperclipai/paperclip Agent Skills author: paperclipai MIT 1 file body ≈ 225 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Use the LLM Wiki plugin tools to maintain a cited local company wiki.

As a process F 33/100 · No process to follow — weak spots: steps, result and completion, when it triggers

ReferenceAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
65
Run on models
none yet
Process rating
F
33/100
No process to follow
Steps w 15
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

    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 · 0

    ✓ No critical or high findings

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

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)

    Process rating: all ten parameters 33/100

    • 0Steps. Prose only: no discrete steps
    • 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
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 40Consistency. Frontmatter name (LLM Wiki Maintainer) differs from the folder (wiki-maintainer)
    • 100Tools and files. No external tools needed
    • 100Execution cost. Instruction body is 225 tokens
    • 100Progress reporting. Reports progress

    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 69: 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
    • +1No license
    • +2Single-language instructions

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.