SKILLEMALL.ai

AC web5-cli

Use when working with Web5 CLI tool for decentralized identity, CKB wallet, DID management, PDS data operations, account creation, posting, profile updates

modbender/skill-library-mcp Agent Skills author: modbender MIT 3 files body ≈ 1 972 tokens Open the sourcegithub.com analyzed 2 d ago

Use when working with Web5 CLI tool for decentralized identity, CKB wallet, DID management, PDS data operations, account creation, posting, profile updates

As a process C 56/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, progress reporting

IntegrationSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
97
Quality 40%
90
Run on models
none yet
Process rating
C
56/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
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 · 3

    ✓ No critical or high findings

    Medium and low: 3
    • low Obfuscation obf-base64-blob scripts/create_account.py:207
      Long base64-looking blob (quoted — discussed, not commanded)
      "accessJwt": "eyJh…ZGl
      quoted
    • low Obfuscation obf-base64-blob scripts/create_account.py:208
      Long base64-looking blob (quoted — discussed, not commanded)
      "refreshJwt": "eyJh…iZG
      quoted
    • low Obfuscation obf-base64-blob scripts/create_account.py:244
      Long base64-looking blob (quoted — discussed, not commanded)
      pds write --pds web5…dev --accessJwt eyJh…Hho
      quoted

    Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 56/100

    • 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
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 85Steps. 37 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1972 tokens
    • 100Running it twice. Mutating operations check current state
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 10 top-level sections: this looks like several domains in one skill
    • high The skill tells the model to perform an irreversible action with no human approval
    • low The response is described with custom markup (16 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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 155: enough signal without eating the budget
    • +4Structure: 20 headings
    • +3Step-by-step instructions: 37 items
    • +3Output format is stated explicitly
    • +4Has examples (16 code blocks)
    • +3All 2 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.