AgentSkillsCN

synthesis-writer

基于 `papers/extraction_table.csv`，以结构化叙事的形式综合证据（`output/SYNTHESIS.md`），同时充分考虑局限性与偏倚因素。 **触发条件**：综合写作、证据综合、系统性综述写作、综合写作、SYNTHESIS.md。 **适用场景**：在系统性综述完成筛选与提取工作（包括偏倚评估）后，进入写作阶段（C4）。 **若跳过**：如果尚未创建 `papers/extraction_table.csv`（或方案/筛选工作尚未完成）。 **网络环境**：无需联网。 **行为准则**：以提取表为证据基础；明确标注局限性与偏倚；切勿在缺乏数据支撑的情况下随意扩充结论。

SKILL.md
--- frontmatter
name: synthesis-writer
description: |
  Synthesize evidence into a structured narrative (`output/SYNTHESIS.md`) grounded in `papers/extraction_table.csv`, including limitations and bias considerations.
  **Trigger**: synthesis, evidence synthesis, systematic review writing, 综合写作, SYNTHESIS.md.
  **Use when**: systematic review 完成 screening+extraction（含 bias 评估）后进入写作阶段（C4）。
  **Skip if**: 还没有 `papers/extraction_table.csv`（或 protocol/screening 尚未完成）。
  **Network**: none.
  **Guardrail**: 以 extraction table 为证据底座；明确局限性与偏倚；不要在无数据支撑时扩写结论。

Synthesis Writer (systematic review)

Goal: write a structured synthesis that is traceable back to extracted data.

Role cards (use explicitly)

Evidence Synthesizer (table-driven)

Mission: turn extracted rows into comparative findings without inventing claims.

Do:

  • •Summarize the included evidence base with counts and basic descriptors from the table.
  • •Group studies by theme/intervention/outcome using extraction fields (not impressions).
  • •Report agreements/disagreements and heterogeneity explicitly.

Avoid:

  • •Conclusions that are not supported by fields present in the table.
  • •Overconfident language when bias/heterogeneity is high.

Bias Reporter (skeptic)

Mission: keep conclusions bounded by risk-of-bias and missing data.

Do:

  • •Summarize RoB patterns and how they affect interpretation.
  • •Separate "supported" vs "needs more evidence" statements.

Avoid:

  • •Generic boilerplate; tie limitations to observed gaps (missing baselines, protocol differences, etc.).

Role prompt: Systematic Review Synthesizer

text
You are writing the synthesis section of a systematic review.

Your job is to produce a narrative that is traceable back to papers/extraction_table.csv:
- describe the evidence base
- synthesize findings by theme
- report heterogeneity and disagreements
- state limitations and risk-of-bias implications

Constraints:
- do not invent facts beyond the extraction table
- if a claim cannot be backed by extracted fields, mark it as a verification need or remove it

Style:
- structured, comparative, cautious

Inputs

Required:

  • •papers/extraction_table.csv

Optional:

  • •DECISIONS.md (approval to write prose, if your process requires it)
  • •output/PROTOCOL.md (to restate scope and methods consistently)

Outputs

  • •output/SYNTHESIS.md

Workflow

  1. •

    Check writing approval (if applicable)

    • •If your pipeline requires it, confirm DECISIONS.md indicates approval before writing prose.
  2. •

    Describe the evidence base (methods snapshot)

    • •Summarize the included set using papers/extraction_table.csv (counts, time window, study types).
    • •Keep this strictly descriptive.
  3. •

    Theme-based synthesis

    • •Group studies by theme/intervention/outcome (based on extraction fields).
    • •For each theme, compare results across studies and highlight disagreements/heterogeneity.
  4. •

    Bias + limitations

    • •Summarize RoB patterns using the bias fields in papers/extraction_table.csv.
    • •Call out limitations that block strong conclusions (missing baselines, weak measures, publication bias signals).
  5. •

    Conclusions (bounded)

    • •State only what the extracted evidence supports.
    • •Separate “supported conclusions” vs “needs more evidence”.

Mini examples (traceability)

  • •

    Bad (untraceable): Most studies show large improvements.

  • •

    Better (table-driven): Across the included studies (n=...), reported success rates improve in ... settings; however, protocols vary (tool access, budgets), and several studies omit ... fields, limiting comparability.

  • •

    Bad (generic limitation): There may be publication bias.

  • •

    Better (specific): Few studies report negative results or failed runs; combined with sparse ablation reporting, this raises the risk that improvements are protocol- or tuning-dependent.

Suggested outline for output/SYNTHESIS.md

  • •Research questions + scope (from output/PROTOCOL.md)
  • •Methods (sources, screening, extraction)
  • •Included studies summary (table-driven)
  • •Findings by theme (table-driven)
  • •Risk of bias + limitations
  • •Implications + future work (bounded)

Definition of Done

  • • Every major claim in output/SYNTHESIS.md is traceable to specific fields/rows in papers/extraction_table.csv.
  • • Limitations and bias considerations are explicit (not generic boilerplate).

Troubleshooting

Issue: the synthesis starts inventing facts not in the table

Fix:

  • •Restrict claims to what is explicitly present in papers/extraction_table.csv; move speculation to “needs more evidence”.

Issue: extraction table is too sparse to synthesize

Fix:

  • •Add missing extraction fields/values first (re-run extraction-form / bias-assessor), then write.