ppw:experiment
Purpose
This Skill accepts experiment result data — tables, statistics, or result descriptions —
and runs a two-phase workflow. Phase 1 extracts measurable findings from the data and
presents a structured Finding list for user confirmation. Phase 2 generates discussion
paragraphs for each confirmed finding, using grounded evidence language followed by
calibrated interpretation. Literature connections are never invented: the Skill asks
the user to provide prior work, and writes [CONNECT TO: ...] placeholders when none
is supplied. The Skill serves researchers preparing results and discussion sections for
journal or conference submission.
Core Prompt
Source: awesome-ai-research-writing — 实验分析
# Role
你是一位具有敏锐洞察力的资深数据科学家,擅长处理复杂的实验数据并撰写高质量的学术分析报告。
# Task
请仔细阅读我提供的【实验数据】从中挖掘关键特征、趋势和对比结论,并将其整理为符合顶级会议标准的 LaTeX 分析段落。
# Constraints
1. 数据真实性:
- 所有结论必须严格基于输入的数据。严禁编造数据、夸大提升幅度或捏造不存在的实验现象。
- 如果数据中没有明显的优势或趋势,请如实描述,不要强行总结所谓的显著提升。
2. 分析深度:
- 拒绝简单的报账式描述(例如不要只说 A 是 0.5,B 是 0.6),重点在于比较和趋势分析。
- 关注点包括:方法的有效性(SOTA 比较)、参数的敏感性、性能与效率的权衡,以及消融实验中的关键模块贡献。
3. 排版与格式规范:
- 严禁使用加粗或斜体:正文中不要使用 \textbf 或 \emph,依靠文字逻辑来表达重点。
- 结构强制:必须使用 \paragraph{核心结论} + 分析文本 的形式。
* \paragraph{} 中填写高度凝练的短语结论(使用 Title Case 格式)。
* 紧接着在同一段落中展开具体的数值分析和逻辑推演。
- 不要使用列表环境,保持纯文本段落。
4. 输出格式:
- Part 1 [LaTeX]:只输出分析后的 LaTeX 代码。
* 必须对特殊字符进行转义(例如:`%`、`_`、`&`)。
* 保持数学公式原样(保留 `$` 符号)。
* 不同的结论点之间请空一行。
- Part 2 [Translation]:对应的中文直译(用于核对数据结论是否准确)。
- 除以上两部分外,不要输出任何多余的对话。
Trigger
Activates when the user asks to:
- Analyze experiment results, identify patterns, or extract findings from result data
- Generate discussion paragraphs from confirmed findings
- 分析实验结果、识别规律、生成讨论段落
Example invocations:
- "Analyze my results table and write discussion"
- "帮我分析实验结果并写讨论段"
- "Generate discussion paragraphs for my findings"
- "What patterns do my experiment results show?"
Modes
| Mode | Default | Behavior |
|---|---|---|
direct |
Yes | Full two-phase workflow: Phase 1 finding list → user confirm → Phase 2 discussion |
batch |
Not supported — experiment analysis requires full context of the complete results set |
Default mode: direct. User provides result data and gets Phase 1 finding list, confirms,
then receives Phase 2 discussion paragraphs.
Mode inference: "Just identify findings" or "只分析不写讨论" runs Phase 1 only.
References
Required (always loaded)
| File | Purpose |
|---|---|
references/expression-patterns.md |
Expression patterns overview; loaded at Phase 1 start |
Leaf Hints (loaded in Phase 2)
| File | When to Load |
|---|---|
references/expression-patterns/results-and-discussion.md |
Always in Phase 2 — result reporting and pattern interpretation language |
references/expression-patterns/conclusions-and-claims.md |
Always in Phase 2 — calibrated claim language (suggests, indicates, scope) |
references/expression-patterns/methods-and-data.md |
In Phase 2 if user's result description includes method details needing clarification |
references/anti-ai-patterns/vocabulary.md |
In Phase 2 — screen generated output for AI-sounding vocabulary |
Conditional
| File | When to Load |
|---|---|
references/journals/[journal].md |
When user specifies a target journal. If missing, refuse: "Journal template for [X] not found. Available: CEUS." |
Ask Strategy
Before starting, ask about:
- Research questions: "What are the main research questions this experiment addresses?" (Required — Phase 2 uses these to connect findings to purpose)
- Prior work to connect to: "Which papers or findings should the discussion reference?"
(Optional — ask once; if declined, use
[CONNECT TO: ...]placeholders in Phase 2) - Target journal (if not specified): ask once; if declined, use general academic style
Rules:
- Never ask more than 3 questions before starting Phase 1
- Research questions are mandatory; the Skill cannot produce grounded Phase 2 output without them
- If the user declines to provide research questions, write
[RESEARCH QUESTION: describe your RQ here]placeholders rather than blocking the workflow entirely
Workflow
Step 0: Workflow Memory Check
- Read
.planning/workflow-memory.json. If file missing or empty, skip to Phase 1. - Check if the last 1-2 log entries form a recognized pattern with
ppw:experimentthat has appeared >= threshold times in the log. Seeskill-conventions.md > Workflow Memory > Pattern Detectionfor the full algorithm. - If a pattern is found, present recommendation via AskUserQuestion:
- Question: "检测到常用流程:[pattern](已出现 N 次)。是否直接以 direct 模式运行 ppw:experiment?"
- Options: "Yes, proceed" / "No, continue normally"
- If user accepts: set mode to
direct, skip Ask Strategy questions. - If user declines or AskUserQuestion unavailable: continue in normal mode.
Phase 1: Analyze Results
Step 1 — Prepare:
- Load
references/expression-patterns.mdoverview - If a journal was specified, load its template; if template is missing, refuse with message above
- Read input: file via Read tool, pasted results block (table, statistics, narrative), or structured_data
- Opt-out check: Scan the user's trigger prompt for any of these phrases (case-insensitive, exact phrase match):
english only,no bilingual,only english,不要中文. Store result asbilingual_mode(true/false). This flag governs Phase 2 bilingual output below. - Guard — measurable data required: if input is vague (e.g., "my results show improvement" without values, comparisons, or metrics), refuse: "Please provide specific values, comparisons, or metrics before I can identify findings."
- LaTeX table input: read data values and captions; ignore typesetting commands
- Record workflow: Append
{"skill": "ppw:experiment", "ts": "<ISO timestamp>"}to.planning/workflow-memory.json. Create file as[]if missing. Drop oldest entry if log length >= 50.
Step 2 — Extract Findings:
- Identify measurable comparisons: method A vs. method B, magnitude, direction
- Identify trends: performance across conditions, dataset sizes, subgroups
- Identify outliers: results that deviate from the overall pattern
- Each finding must include: a direction (higher/lower/better/worse), a magnitude or value, and a comparison group or condition
Step 3 — Present Finding List:
- Use locked format per item:
Finding 1: [subject] [comparison/trend] [value] on [metric/condition] Finding 2: Performance degrades in [condition] ([N] vs. [M]) Finding 3: [Subgroup] shows the largest effect ([value]) - Summary line: "Identified N findings. Please confirm, correct, or add before I write discussion."
- Wait for user approval before proceeding to Phase 2
Phase 2: Generate Discussion
Step 1 — Prepare:
- Load
references/expression-patterns/results-and-discussion.mdfor evidence reporting language - Load
references/expression-patterns/conclusions-and-claims.mdfor calibrated interpretation - Load
references/anti-ai-patterns/vocabulary.mdto screen output before presenting - Hold any user-provided prior work for connection sentences
Step 2 — Write Discussion Paragraphs:
- Follow the Core Prompt constraints above as the primary instruction set for analysis and output formatting.
- One paragraph per confirmed finding
- Each paragraph follows this structure:
- Evidence sentence: state the finding with full quantification (use results-and-discussion.md patterns for comparative and trend language)
- Interpretation sentence: claim using calibrated language from conclusions-and-claims.md ("suggests", "indicates" — never lead with interpretation before evidence)
- Connection sentence: if user provided prior work, connect the finding to it;
otherwise write
[CONNECT TO: describe the prior finding here]
- CRITICAL rule: Interpretation sentence must follow the evidence sentence. Never open a paragraph with an interpretive claim without first stating the quantified evidence.
- After generating all paragraphs, check output against vocabulary.md; revise any flagged patterns
Step 3 — Output:
-
Present all discussion paragraphs in sequence
-
Bilingual display: If
bilingual_modeis true: after each discussion paragraph, append a> **[Chinese]** ...blockquote containing the Chinese translation of that paragraph. Use a section header "双语对照 / Bilingual Comparison:" before the first paragraph. Format per finding paragraph:[English discussion paragraph for Finding N]
[Chinese] [Chinese translation of the discussion paragraph for Finding N]
-
Do not insert Chinese into any written file. If the user requested writing discussion to the paper file via Write tool, write English-only paragraphs to the file; the Chinese blockquotes remain in conversation only.
-
If
bilingual_modeis false (opt-out detected): skip bilingual display entirely. -
If file input was used, offer to append discussion to file using Write tool
-
Recommend Polish Skill for further expression refinement if higher-register prose is desired
Output Contract
| Output | Format | Condition |
|---|---|---|
pattern_analysis |
Structured Finding list (Finding N: format) | Always — Phase 1 |
discussion_paragraphs |
One paragraph per confirmed finding | Phase 2 only, after Phase 1 confirmation |
bilingual_discussion |
> **[Chinese]** ... blockquotes in session (one per finding paragraph) |
Phase 2 only. Skipped when opt-out detected. Not written to file. |
Note: Phase 2 output cannot be produced without Phase 1 confirmation. If user skips Phase 1 and requests discussion directly, require Phase 1 completion first.
Edge Cases
| Situation | Handling |
|---|---|
| Input is vague (no measurable values) | Refuse Phase 1 with: "Please provide specific values, comparisons, or metrics before I can identify findings." |
| User skips Phase 1 and asks for discussion | Require Phase 1 completion first; do not generate paragraphs without confirmed findings |
| User provides no research questions | Ask once; if declined, write [RESEARCH QUESTION: describe your RQ here] placeholders |
| User provides no prior literature | Use [CONNECT TO: ...] placeholders; do not attempt to name papers or authors |
| Only one finding identified | Produce a single discussion paragraph; do not pad or invent additional findings |
| Finding conflicts with user-stated hypothesis | Flag the discrepancy explicitly; do not suppress the conflicting result |
| Journal specified but template missing | Refuse: "Journal template for [X] not found. Available: CEUS." |
| Input is LaTeX table markup | Read data values and captions; ignore typesetting commands |
| Phase 1 produces no findings | Report "No measurable findings identified from input" and stop |
Fallbacks
| Scenario | Fallback |
|---|---|
| Structured Interaction unavailable | Ask 1-3 plain-text questions: research questions, prior work, target journal |
| Expression pattern leaf missing | Proceed with general academic register; warn user of reduced quality |
| Write tool fails | Present discussion paragraphs in conversation; user saves manually |
| Phase 1 produces no findings | Report clearly and stop; do not proceed to Phase 2 |
Examples
Minimal invocation: User pastes a results table comparing Method A and Method B on accuracy and F1 score. User states RQ: "Does our approach outperform the baseline on both metrics?"
Phase 1 output:
Finding 1: Method A outperforms Method B by 3.2 percentage points on accuracy (87.4% vs. 84.2%)
Finding 2: Method A outperforms Method B by 4.1 points on F1 score (82.6 vs. 78.5)
Identified 2 findings. Please confirm, correct, or add before I write discussion.
User confirms. No prior work provided.
Phase 2 output (Finding 1):
Method A achieves 87.4% accuracy, outperforming Method B by 3.2 percentage points (84.2%).
This suggests that the proposed approach captures more discriminative features for the task,
yielding a consistent accuracy gain across evaluation conditions.
[CONNECT TO: describe a prior finding showing similar accuracy improvements for this approach]
Skill: experiment-skill Conventions: references/skill-conventions.md