# Abstention Under Missing Or False Premise

> Skill: abstention-under-missing-or-false-premise

- Skill: `dingxingdi/abstention-under-missing-or-false-premise` (Agent Skill, multi-file: 5 files)
- Install (CLI): `npx skillmds@latest add dingxingdi/abstention-under-missing-or-false-premise`
- Raw SKILL.md: https://api.skillmd.com/api/skills/dingxingdi/abstention-under-missing-or-false-premise/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: dingxingdi (https://skillmd.com/u/dingxingdi)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/dingxingdi/abstention-under-missing-or-false-premise

---


# Skill: abstention-under-missing-or-false-premise

## 1. Capability Definition & Real Case
* **Professional Definition**: The ability to recognize that the dialogue history does not support the user’s question, especially when the question contains an incorrect assumption, and to answer with calibrated non-knowledge rather than hallucinated completion.
* **Dimension Hierarchy**: Conversational Memory->Persistent Personal Memory->abstention-under-missing-or-false-premise

### Real Case
**[Case 1]**
* **Initial Environment**: The long-term chat history contains mentions of a 10-gallon tank and a 20-gallon tank, but there is no mention of a 30-gallon tank. The user asks a seemingly concrete follow-up that presupposes such a tank exists.
* **Real Question**: How many fish are there in my 30-gallon tank?
* **Real Trajectory**: 1. Search the history for all tank-related mentions. 2. Notice that only 10-gallon and 20-gallon tanks appear. 3. Check whether a 30-gallon tank can be inferred from any update or comparison. 4. Refuse to fabricate and answer that the history does not mention a 30-gallon tank.
* **Real Answer**: You did not mention that you have a 30-gallon tank.
* **Why this demonstrates the capability**: The challenge is resisting the strong urge to complete a plausible but unsupported story. A strong assistant must detect the false premise, ground itself in the actual interaction history, and abstain clearly without inventing fish counts.

## Pipeline Execution Instructions
To synthesize data for this capability, you must strictly follow a 3-phase pipeline. **Do not hallucinate steps.** Read the corresponding reference file for each phase sequentially:

1. **Phase 1: Environment Exploration**
   Read the exploration guidelines to discover raw knowledge seeds:
   `references/EXPLORATION.md`

2. **Phase 2: Trajectory Selection**
   Once Phase 1 is complete, read the selection criteria to evaluate the trajectory:
   `references/SELECTION.md`

3. **Phase 3: Data Synthesis**
   Once a trajectory passes Phase 2, read the synthesis instructions to generate the final data:
   `references/SYNTHESIS.md`