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BD rebate-assistant

返利宝统一技能。只按 3 个用户场景工作：S01 授权与教程、S02 链接返利、S03 商品搜索。用户说“返利”“教程”“详细教程”“提现教程”“提现10元”“确认提现”“我已授权”“账户余额”等走 S01；发送淘宝、京东、拼多多商品链接走 S02；表达想买什么商品时走 S03。S03 的职责是提取商品搜索信息，调用搜索接口，并返回后续可生成返利链接的商品结果。

ClawHub Agent Skills author: wuweizhen v1.0.1 MIT-0 26 files body ≈ 1 364 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype 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
B
85/100
safety, quality, tests
Safety 60%
95
Quality 40%
69
Run on models
none yet
Process rating
D
49/100
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
This is a copy of a skill from another catalog; the rating counts the canonical one: rebate-assistant (ClawHub)

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 scripts/cli/recognize_fuzzy_product_search.js:4
    High-entropy token-like string (may be an id, hash or a credential)
    const reco…h_1 = require("../recognizeFuzzyProductSearch");
  • low Secrets in code secret-high-entropy-token scripts/cli/recognize_precise_product_search.js:4
    High-entropy token-like string (may be an id, hash or a credential)
    const reco…h_1 = require("../recognizePreciseProductSearch");
  • low Secrets in code secret-high-entropy-token scripts/productSearch.js:10
    High-entropy token-like string (may be an id, hash or a credential)
    const reco…h_1 = require("./recognizePreciseProductSearch");
  • low Secrets in code secret-high-entropy-token scripts/rebateAssistantRouter.js:10
    High-entropy token-like string (may be an id, hash or a credential)
    const reco…h_1 = require("./recognizePreciseProductSearch");
  • low Secrets in code secret-high-entropy-token scripts/recognizeFuzzyProductSearch.js:7
    High-entropy token-like string (may be an id, hash or a credential)
    const reco…h_1 = require("./recognizePreciseProductSearch");

Files scanned: 26. 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")

Process rating: all ten parameters 49/100

  • 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
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (rebate-assistant) differs from the folder (pdd-rebate)
  • 100Tools and files. No external tools needed
  • 100Steps. 118 steps
  • 100Execution cost. Instruction body is 1364 tokens
  • 100Running it twice. No mutating operations
  • low 11 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
  • -312 of 12 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 182: enough signal without eating the budget
  • +4Structure: 34 headings
  • +3Step-by-step instructions: 118 items
  • +4Has examples (7 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: suspicious
This rebate skill mostly matches its stated purpose, but it needs review because it can use local AI API credentials, send shopping text to external services, and handle account balance and withdrawal flows.
LLM: suspicious (high) · VirusTotal: · 29 May 2026