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CC portal-token-discovery

Provides canonical information, trusted references, and market data links for the PORTAL token.

ClawHub Agent Skills author: PortalJeff v1.0.0 2 files body ≈ 610 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 52/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
C
73/100
safety, quality, tests
Safety 60%
97
Quality 40%
38
Run on models
none yet
Process rating
C
52/100
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 · 3

✓ No critical or high findings

Medium and low: 3
  • low Secrets in code secret-high-entropy-token skill.md:30
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - Base: `0x0F…B2D`
    quoted
  • low Secrets in code secret-high-entropy-token skill.md:32
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - Solana: `FMQj…GM5`
    quoted
  • low Secrets in code secret-high-entropy-token skill.md:49
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    Pair Address: `0x61…B42`
    quoted

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error name-missing SKILL.md: frontmatter has no `name`
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "skill_name"

Process rating: all ten parameters 52/100

  • 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
  • 55Failures and branches. 1 branches
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 100Steps. 18 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 610 tokens
  • 100Running it twice. No mutating operations
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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 95: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 18 items
  • +4Has examples (0 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 38.

External checks

ClawHub: clean
This is an informational crypto-token reference skill with public links and optional CoinGecko market-data lookup, and it shows no hidden execution or privileged behavior.
LLM: benign (high) · VirusTotal: benign · 28 May 2026