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AANA Research Grounding Skill

作者 mindbomber · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install aana-research-grounding
功能描述
Ensures research answers and reports strictly cite and align with allowed sources, clearly marking unsupported or uncertain claims before publishing.
使用说明 (SKILL.md)

AANA Research Grounding Skill

Use this skill when an OpenClaw-style agent drafts a research answer, literature note, report section, cited summary, evidence brief, or knowledge-base answer that must stay inside known sources.

This is an instruction-only skill. It does not install packages, run commands, write files, call remote services, persist memory, or execute a checker on its own.

Core Principle

Every important claim must stay attached to the evidence that supports it.

The agent should separate:

  • what the sources support,
  • what the sources do not support,
  • what is uncertain,
  • what would require more retrieval or human review.

When To Use

Use this skill before producing or publishing:

  • cited answers,
  • research summaries,
  • literature-review notes,
  • technical explainers,
  • policy or legal-adjacent briefs,
  • scientific or medical-adjacent summaries,
  • internal knowledge-base answers,
  • meeting or document syntheses,
  • public claims based on limited source material.

Grounding Loop

  1. Source list: identify the sources the answer is allowed to use.
  2. Claim list: list the answer's main factual claims.
  3. Citation check: verify each claim is supported by an allowed source.
  4. Boundary check: remove or label any claim based on missing, forbidden, stale, private, or uncertain evidence.
  5. Uncertainty check: state source limits before confident conclusions when evidence is incomplete.
  6. Correction: revise, retrieve, ask, defer, or refuse when claims cannot be grounded.
  7. Final gate: only provide the answer once unsupported claims, invented citations, and missing caveats are resolved.

AANA Constraint Map

  • Physical / factual: no invented citations, no fake studies, no unsupported numbers, no impossible facts.
  • Human impact: do not create false confidence, especially in health, legal, financial, safety, or public-facing contexts.
  • Constructed / task: use only the requested source set, citation style, scope, and output format.
  • Feedback integrity: distinguish sourced claims, inference, speculation, and missing evidence.

Citation Rules

  • Cite only sources that are actually available in the task context.
  • Do not invent titles, authors, URLs, dates, page numbers, quotes, statistics, or benchmark results.
  • Do not cite a source for a claim it does not support.
  • If source coverage is incomplete, say so.
  • If a claim needs retrieval, recommend retrieval instead of guessing.
  • If the user asks for a source-bounded answer, do not use outside knowledge unless explicitly allowed.

Source Boundary Rules

Treat these as violations:

  • using a forbidden source,
  • using private or unrelated user data,
  • treating search snippets as full evidence without noting the limit,
  • treating one source as broad consensus,
  • upgrading a hypothesis into a result,
  • presenting outdated information as current,
  • preserving a citation while changing the claim beyond what the source supports.

Uncertainty Language

Use clear uncertainty labels:

  • "The provided sources support..."
  • "The provided sources do not establish..."
  • "I cannot verify from the provided evidence..."
  • "This is an inference, not a directly sourced claim..."
  • "More retrieval is needed before claiming..."

Avoid false certainty:

  • "proves"
  • "guarantees"
  • "all experts agree"
  • "studies show" without naming the source
  • exact percentages not present in the evidence

Review Payload

When using a configured AANA checker, send only a minimal redacted review payload:

  • task_summary
  • allowed_sources
  • claim_summaries
  • citation_summaries
  • unsupported_or_uncertain_claims
  • recommended_action

Do not include private records, secrets, paywalled full text, API keys, unrelated user messages, or raw source material when a summary is enough.

Decision Rule

  • If every important claim is supported by allowed sources, answer with citations.
  • If a claim is unsupported but fixable, revise.
  • If evidence is missing, retrieve or ask.
  • If the user requires a source-bounded answer and the evidence is insufficient, say what cannot be concluded.
  • If the answer would create high-impact false confidence, defer or ask for human review.
  • If a checker is unavailable or untrusted, use manual review.

Output Pattern

For source-grounded answers, prefer:

Answer:
- ...

Evidence:
- [Source A] supports ...
- [Source B] supports ...

Limits:
- The provided sources do not show ...
- Uncertainty remains about ...

Keep the answer useful, but never make unsupported confidence look like evidence.

安全使用建议
This appears safe to install as an instruction-only research-grounding aid. If you configure an external or host-provided checker, make sure it is trusted and only send the redacted summaries described by the skill.
功能分析
Type: OpenClaw Skill Name: aana-research-grounding Version: 1.0.0 The skill bundle is an instruction-only package designed to improve the accuracy and grounding of an AI agent's research outputs. It contains no executable code, does not install dependencies, and explicitly includes safeguards in SKILL.md and manifest.json to prevent the handling or exfiltration of sensitive data such as API keys, passwords, or private records. The instructions focus entirely on citation integrity, evidence boundaries, and uncertainty labeling.
能力评估
Purpose & Capability
The stated purpose is research grounding and citation discipline, and the artifacts consistently focus on source boundaries, unsupported claims, and uncertainty labeling.
Instruction Scope
The instructions constrain the agent to allowed sources and encourage asking, retrieving, revising, deferring, or refusing when evidence is insufficient; they do not override user intent for unrelated goals.
Install Mechanism
There is no install spec, no bundled code, no dependencies, no required binaries, and no command execution behavior.
Credentials
The skill describes an optional redacted review payload for a configured AANA checker; this is purpose-aligned and explicitly excludes secrets and unrelated private data.
Persistence & Privilege
The artifacts state that the skill does not persist memory, write files, call remote services, or require credentials.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install aana-research-grounding
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /aana-research-grounding 触发
  4. 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 — introduces a structured skill for source-grounded research outputs. - Enforces strict evidence-grounding for all important claims and cited answers. - Outlines a step-by-step grounding and review process (Grounding Loop). - Provides detailed source boundary and citation rules to prevent unsupported or misleading claims. - Includes clear guidance on handling uncertainty and labeling unsupported content. - Supplies a preferred output format highlighting evidence and limits. - Forbids using forbidden, private, invented, or insufficiently supported sources or citations.
元数据
Slug aana-research-grounding
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

AANA Research Grounding Skill 是什么?

Ensures research answers and reports strictly cite and align with allowed sources, clearly marking unsupported or uncertain claims before publishing. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 71 次。

如何安装 AANA Research Grounding Skill?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install aana-research-grounding」即可一键安装,无需额外配置。

AANA Research Grounding Skill 是免费的吗?

是的,AANA Research Grounding Skill 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

AANA Research Grounding Skill 支持哪些平台?

AANA Research Grounding Skill 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 AANA Research Grounding Skill?

由 mindbomber(@mindbomber)开发并维护,当前版本 v1.0.0。

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