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Yao 2022 React

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Use ReAct's interleaved action and observation pattern for evidence-carrying tool work. NOT for treating model reasoning traces as evidence without checking the tool observations.

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  • Added September 24, 2026
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SKILL.md
---
license: Apache-2.0
name: yao-2022-react
description: Use ReAct's interleaved action and observation pattern for evidence-carrying tool work. NOT for treating model reasoning traces as evidence without checking the tool observations.
metadata:
  category: Research & Academic
  tags: [react-prompting, reasoning, acting, llm-agents, tool-use]
---

# ReAct: decisions grounded by tool observations

Yao et al.'s [ReAct paper](https://arxiv.org/html/2210.03629v3) interleaves generated reasoning, actions, and observations in question answering and interactive environments. Treat its trace as a control pattern: model text proposes the next action, while a tool result supplies external evidence. It does not prove that generated rationale is faithful, that a tool call is authorized, or that grounding guarantees correctness.

Use short decision summaries: goal, uncertainty, chosen action, and what observation would resolve it. Do not require a model to expose private chain-of-thought; retain the tool request, tool result, citations, and a concise user-safe explanation sufficient to audit a result.

## Evidence-carrying loop

```mermaid
flowchart TB
  G[User goal] --> D[Decision summary: gap and next action]
  D --> A{Action authorized and valid?}
  A -- no --> Z[State limitation or abstain]
  A -- yes --> O[External observation]
  O --> E[Evidence ledger: source, time, limits]
  E --> U[Updated decision summary]
  U --> C{Claim supported?}
  C -- yes --> R[Answer with cited observation]
  C -- no --> Q{Justified follow-up within budget?}
  Q -- yes --> D
  Q -- no --> Z
```

```mermaid
sequenceDiagram
  participant U as User
  participant M as Agent
  participant T as Authorized tool
  participant L as Evidence ledger
  U->>M: factual question
  M->>T: scoped query
  T-->>M: result plus source
  M->>L: record request, result, source, limitation
  M-->>U: claim tied to source or abstention
```

## Compact trace fixture

```text
goal: identify whether a claim is supported
decision: source A is incomplete; query source B for the missing fact
action: search({query: "...", scope: "approved corpus"})
observation: {source: "B", excerpt_id: "B-17", result: "conflicts with A"}
next: do not assert the claim; seek a primary source or say evidence conflicts
```

The decision is not evidence. The observation's source and retrieval context are. If a result is empty, malformed, or outside the authorized corpus, record that limitation and either reformulate a bounded query or abstain.

## Design rules

- Validate action schemas and authorization outside the language model. Tool availability is not permission.
- Carry raw tool receipts or stable excerpts into the evidence ledger; a later summary must not be the only provenance.
- Use a state-derived loop guard (repeated action, unchanged observation, or budget selected by the application), then stop or escalate through an existing policy.
- Human correction may change a decision or final assertion; retain the correction and supporting evidence. It must not silently rewrite historical tool results.
- Benchmark figures in the paper apply to named datasets, prompts, and models; do not convert them to universal error or hallucination rates.

## Source-grounded navigation

- [Reasoning/action trace and limits](references/reasoning-action-synergy-in-agent-systems.md)
- [Evidence versus generated text](references/bridging-knowledge-and-action-gap.md)
- [Failure propagation and recovery](references/failure-modes-and-error-propagation.md)
- [Uncertainty as a query or abstention trigger](references/uncertainty-and-confidence-in-agent-decisions.md)
- [Interpretable operational traces](references/human-interpretability-and-controllability.md)
- [Source evaluation and controller contract](references/source-evaluation-and-controller-contract.md)

## Boundaries

ReAct is a prompting and interaction pattern, not a substitute for authorization, source validation, privacy review, or effect confirmation.

## Bundle navigation

[diagrams index](diagrams/INDEX.md).

Files in this skill

  • SKILL.md11.1 KB
  • _book_identity.json3.1 KB
  • diagrams/01_flowchart_react_decision_loop-_when_to_r.md2.6 KB
  • diagrams/02_sequenceDiagram_agent_reasoning-action-correct.md2 KB
  • diagrams/03_quadrantChart_confidence-based_knowledge_sou.md700 B
  • diagrams/INDEX.md950 B
  • references/INDEX.md1.5 KB
  • references/bridging-knowledge-and-action-gap.md12.6 KB
  • references/decomposition-through-explicit-subgoaling.md11.7 KB
  • references/failure-modes-and-error-propagation.md12.6 KB
  • references/hierarchical-abstraction-in-agent-reasoning.md12.4 KB
  • references/human-interpretability-and-controllability.md12.7 KB
  • references/learning-reasoning-acting-patterns.md11.5 KB
  • references/reasoning-action-synergy-in-agent-systems.md11.9 KB
  • references/uncertainty-and-confidence-in-agent-decisions.md12.1 KB

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