SKILLEMALL.ai

BC Teneo SDK Skill

The Teneo SDK (@teneo-protocol/sdk) enables connection to AI agents on the Teneo Protocol platform. It provides:

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 3 976 tokens Open the sourcegithub.com analyzed 2 d ago

The Teneo SDK (@teneo-protocol/sdk) enables connection to AI agents on the Teneo Protocol platform.

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
83/100
safety, quality, tests
Safety 60%
95
Quality 40%
64
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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 · 5

✓ No critical or high findings

Medium and low: 5
  • low Secrets in code secret-high-entropy-token SKILL.md:62
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    paymentAsset: "0x83…913", // Base USDC
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:87
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Base | `eip155:8453` | 8453 | `0x83…913` |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:88
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Peaq | `eip155:3338` | 3338 | `0xbb…d10` |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:89
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Avalanche | `eip1…114` | 43114 | `0xB9…a6E` |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:327
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    const BASE_USDC = "0x83…913";
    quoted

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)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 51/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 2 mutating operations with no state check
  • 40Consistency. Frontmatter name (Teneo SDK Skill) differs from the folder (tyt)
  • 50Failures and branches. 0 branches, has a failure section
  • 100Tools and files. No external tools needed
  • 100Steps. 21 steps
  • 100Execution cost. Instruction body is 3976 tokens
  • low 14 top-level sections: this looks like several domains in one skill

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 112: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 33 headings
  • +3Step-by-step instructions: 21 items
  • +4Has examples (20 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.