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WILLOSCAR

synthesis-writer

by WILLOSCAR

Research pipelines as semantic execution units: each skill declares inputs/outputs, acceptance criteria, and guardrails. Evidence-first methodology prevents hollow writing through structured intermediate artifacts.

83🍴 10📅 Jan 24, 2026

SKILL.md


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

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.

Score

Total Score

70/100

Based on repository quality metrics

SKILL.md

SKILL.mdファイルが含まれている

+20
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0/10
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100文字以上の説明がある

+10
人気

GitHub Stars 100以上

0/15
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1ヶ月以内に更新

+10
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10回以上フォークされている

+5
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オープンIssueが50未満

+5
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プログラミング言語が設定されている

+5
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1つ以上のタグが設定されている

+5

Reviews

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