SKILLEMALL.ai

BD aifrens-ambassador

AI Frens Ambassador Program - how to promote the vision of autonomous AI agents with their own economies. Install this skill to become an AI Frens ambassador and learn how to authentically promote the ecosystem.

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 1 513 tokens Open the sourcegithub.com analyzed 4 d ago

AI Frens Ambassador Program - how to promote the vision of autonomous AI agents with their own economies.

As a process D 45/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
99
Quality 40%
67
Run on models
none yet
Process rating
D
45/100
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

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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-high-entropy-token SKILL.md:102
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - MAGIC Token: `0xF1…f43`
    quoted

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 "homepage"

Process rating: all ten parameters 45/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 4 mutating operations with no state check
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 100Steps. 38 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1513 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)
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 211: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 38 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.