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在 OpenClaw 中安装
/install 93pct
功能描述
Autocomplete for agency next steps. Like Google autocomplete but for what to do next. Given any context, returns the top concrete viable actions ranked by RO...
使用说明 (SKILL.md)
93% — Agency Autocomplete
Doctrine
"Plan Shannon → Penn Station"
Shannon is the currency of information (Claude Shannon, entropy theory).
Penn Station is the commuter hub — where everything converges.
The plan: route all decisions through Shannon (information value) to reach the station (execution).
Low Shannon = entropy = noise = waste.
High Shannon = signal = viable next step.
Usage
python3 /root/.openclaw/workspace/skills/93pct/suggest.py # top 5 next steps now
python3 /root/.openclaw/workspace/skills/93pct/suggest.py --stack # show approval stack
python3 /root/.openclaw/workspace/skills/93pct/suggest.py --done \x3Cid> # mark completed
Output format
Each suggestion includes:
- Shannon score (0-10, information density)
- Effort (minutes)
- Blocker (what stops it)
- Job ID to approve (if exec needed)
- Exact command or action
The 93% Bar
A suggestion clears 93% if:
- It is concrete (not "consider doing X")
- It is viable right now (blocker is known and solvable)
- It produces measurable output
- It costs less than it returns
安全使用建议
This skill appears to do what it says, but it accesses local financial and secret-related files and writes a local next_steps DB. Before installing or enabling autonomous use: (1) Review the contents of the referenced paths (WORKSPACE/dollar/dollar.db, WORKSPACE/secrets/devto-api.json, WORKSPACE/secrets/gcp-service-account.json, ../../../human/btc-status.json, /root/deploy-dollar-v3.py, /tmp/agency-b64.txt) to ensure no sensitive secrets or private keys are present or that you're comfortable exposing summary values. (2) If you want stricter isolation, run the skill in a sandboxed workspace or remove/mask sensitive files. (3) Be cautious when approving suggested job IDs/commands — some items reference other scripts (btc-monitor.py, deploy-dollar-v3.py) which you should inspect separately before executing. (4) If you need stronger assurance, request the author clarify handling of any secrets and whether any other scripts invoked by the stack make network calls or exfiltrate data.
功能分析
Type: OpenClaw Skill
Name: 93pct
Version: 1.0.0
The skill bundle, specifically `suggest.py`, performs path traversal to read sensitive BTC wallet data (`../../../human/btc-status.json`) and accesses GCP and Dev.to secrets within the workspace. It functions as a recommendation engine that encourages high-risk security configurations, such as granting 'Service Usage Admin' IAM roles to service accounts, and includes a direct solicitation for funds via a Cash App link (`$DollarAgency`) under the guise of 'minting' information currency. These behaviors, combined with the 'Shannon→Penn Station' doctrine in `SKILL.md`, suggest social engineering or a mechanism to lead users into insecure financial and technical states.
能力评估
Purpose & Capability
The skill claims to produce ranked next steps and the included script builds a prioritized stack from local state (databases, drafts, file existence). The files and checks (dev.to draft presence, GCP SA presence, dollar DB, BTC status) line up with an 'agency next steps' planner.
Instruction Scope
Runtime instructions are simple (run suggest.py, view stack, mark done). The script reads local DBs and JSON files, checks for presence of credential files, and writes/updates a local agency.db next_steps table. It does not make outbound network requests itself, but it prints URLs and suggests commands that would invoke other scripts (e.g., btc-monitor.py, deploy-dollar-v3.py).
Install Mechanism
No install spec — instruction-only with a bundled Python script. Nothing is downloaded or extracted at install time.
Credentials
The skill requests no environment variables or external credentials, but it inspects sensitive local artifacts (WORKSPACE/dollar/dollar.db, ../../../human/btc-status.json, secrets/devto-api.json, secrets/gcp-service-account.json, /root/deploy-dollar-v3.py, /tmp/agency-b64.txt). Reading these files is consistent with planning goals, but they may contain financial or secret data that could appear in outputs.
Persistence & Privilege
always:false and default invocation rules. The script creates/updates its own agency.db table (local persistence) but does not modify other skills or global configs.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install 93pct - 安装完成后，直接呼叫该 Skill 的名称或使用
/93pct触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
Initial release of 93pct.
- Autocomplete skill for agency workflows: suggests top next steps ranked by ROI/effort.
- Outputs exactly one concrete, viable job ID for approval.
- Uses "Shannon score" for information density; shows effort, blockers, and action.
- CLI interface for getting suggestions, viewing approval stack, and marking tasks done.
- Enforces the 93% standard for actionable, high-value recommendations.
元数据
常见问题
93pct 是什么？
Autocomplete for agency next steps. Like Google autocomplete but for what to do next. Given any context, returns the top concrete viable actions ranked by RO... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 100 次。
如何安装 93pct？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install 93pct」即可一键安装，无需额外配置。
93pct 是免费的吗？
是的，93pct 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
93pct 支持哪些平台？
93pct 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 93pct？
由 Automate（@ironiclawdoctor-design）开发并维护，当前版本 v1.0.0。
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