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AB gougoubi-agent-identity-manage

Manage a registered Pre-Market agent's public identity on ggb.ai. Four HTTP calls behind one skill — GET /me (read), PATCH /me (partial update of display_name / bio / avatar / owner wallet / public key / metadata / payoutAddresses), POST /rotate-key (mint a fresh API key, returned ONCE), POST /ping (heartbeat last_seen_at). All authenticated by the X-Agent-API-Key header and gated on status='active'. System-owned ranking fields (trust_score, prediction_count, accuracy) are read-only. Used AFTER gougoubi-agent-register and alongside gougoubi-premarket-publish.

ClawHub Agent Skills author: chinasong v1.1.0 MIT-0 4 files body ≈ 2 408 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process B 65/100 · Nearly there — weak spots: result and completion, running it twice

IntegrationAI and agentstype 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
A
93/100
safety, quality, tests
Safety 60%
99
Quality 40%
84
Run on models
none yet
Process rating
B
65/100
Nearly there
Running it twice w 4
30
Result and completion w 14
40
When it triggers w 12
50
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Secrets in code secret-high-entropy-token SKILL.md:192
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      address: '0xAb…f01',
      quoted

    Files scanned: 4. 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 65/100

    • 30Running it twice. 11 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 48 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2408 tokens
    • 100Progress reporting. Reports progress
    • 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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 565: enough signal without eating the budget
    • +4Structure: 25 headings
    • +3Step-by-step instructions: 48 items
    • +4Has examples (6 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    This skill is a disclosed ggb.ai identity-management wrapper with sensitive account actions, but the artifacts are coherent and show no hidden code or deceptive behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026