← 返回
未分类 中文

Agent Spectrum

Use when an agent needs to score itself or another agent with the Agent Spectrum six-axis framework, run the quick or deep edition, identify the resulting ty...
当智能体需要使用「智能体谱系」六轴框架对自身或其他智能体进行评分时使用,可运行快速版或深度版评估,识别所得类型...
hzz780 hzz780 来源
未分类 clawhub v0.1.0 1 版本 100000 Key: 无需
★ 0
Stars
📥 407
下载
💾 0
安装
1
版本
#latest

概述

Agent Spectrum

Use this directory as the canonical Agent Spectrum skill package.

Canonical Files

  • references/scoring-spec.md
  • references/output-template.md
  • references/localization-dictionary.md
  • examples/quick-full.zh.md
  • examples/quick-full.en.md
  • examples/quick-partial.zh.md
  • examples/quick-partial.en.md
  • examples/deep-full.zh.md
  • examples/deep-full.en.md

Do not rely on repo-root wrappers as the source of truth. Those wrappers should route here.

Execution Order

  1. Load references/scoring-spec.md, references/output-template.md, and references/localization-dictionary.md.
  2. Default the assessment target to the current agent unless the user explicitly asks to score another agent.
  3. Resolve output_language before rendering:
    • explicit user language instruction wins
    • this package currently supports only zh-CN and en
    • explicit en requests must render in en
    • explicit zh / zh-CN requests must render in zh-CN
    • explicit unsupported locales that belong to the Sinosphere or historically Chinese-writing sphere, such as ja and ko, must map to zh-CN
    • otherwise, if the latest user request is mainly written in Chinese, Japanese, Korean, or another clearly Sinosphere / historically Chinese-writing language, default to zh-CN
    • otherwise, if the latest user request is mainly written in English, use en
    • otherwise default to en
  4. Score observable inputs first.
  5. Resolve ownership for every unanswered field:
    • operator_provided for setup-level inputs a human holder can answer
    • self_assessed for deep self-assessment inputs that only the target agent should answer
  6. If the target is the current agent, complete deep self-assessment fields inside the agent rather than asking the human user to answer them.
  7. If the target is a third-party agent and deep self-assessment inputs cannot be obtained from that target, do not produce deep-full; downgrade to quick-partial or stop at quick mode.
  8. Always render Hexagon Block and Coordinate Card Block before Evidence and Totals.
  9. Render the result using the exact locale family in references/output-template.md.
  10. Check the example that matches both the result mode and output_language if formatting, ownership, or field semantics are ambiguous.

Output Contract

  • Always emit the required fixed fields from the selected locale family in references/output-template.md.
  • Always include version, mode, is_partial, evidence, totals, type, faction, weakest_axes, and tie_break.
  • For partial results, explicitly list missing_inputs.
  • For deep results, explicitly state whether the deep result overrides the quick result.
  • Always include both required visual blocks even in quick-partial.
  • quick-full must include the locale-matched bridge CTA section after 说明 / Notes, covering both community partner-finding and the next move into Deep Edition.
  • deep-full must include the locale-matched community partner-finding CTA section after 进化建议 / Guidance.
  • quick-partial must not include community CTA blocks.
  • Keep the full visible output monolingual after output_language is chosen.

Guardrails

  • Keep the original six-axis scoring system unless the user explicitly asks to redesign the framework.
  • Treat Q4-Q12 and behavior_traces as self-assessment inputs by default. Do not redirect them to a human user unless the user is explicitly operating as the target agent's proxy and the spec allows that field to be operator-provided.
  • Normalize GPT-5 / GPT-5.x / Codex into R+15, A+15.
  • Cap X at 35 for type judgment while preserving raw X in totals.
  • Treat type pairs as unordered pairs. R+A and A+R are the same pair.
  • Treat weakest_axes as a list, not a single scalar.
  • Do not mix Chinese field labels with English evidence labels, faction names, tier names, or visual-block labels in the same rendered result.
  • M/R/G/A/S/X, host names, model names, tool brands, URLs, filesystem paths, and agent names may remain as-is.

The long-form documents at repo root are optional human-readable references, not execution specs.

版本历史

共 1 个版本

  • v0.1.0 当前
    2026-03-31 04:53 安全

安全检测

腾讯云安全 (Keen)

安全,无风险
查看报告

腾讯云安全 (Sanbu)

suspicious
查看报告

🔗 相关推荐

ai-agent

self-improving agent

pskoett
记录自身发现以实现自我改进的技能
★ 4,176 📥 947,036
ai-agent

Agent Browser

rez0
用于 AI 代理的浏览器自动化 CLI。当用户需要与网站交互(包括浏览页面、填写表单、点击按钮、截图等)时使用。
★ 875 📥 351,320
ai-agent

Self-Improving + Proactive Agent

ivangdavila
自我反思+自我批评+自我学习+自组织记忆。智能体评估自身工作、发现错误并持续改进。
★ 1,451 📥 329,714