Synthesis Writer (evidence 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, cautiousInputs
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
- Check writing approval (if applicable)
- If your pipeline requires it, confirm DECISIONS.md indicates approval before writing prose.
- Describe the evidence base (methods snapshot)
- Summarize the included set using papers/extraction_table.csv (counts, time window, study types). - Keep this strictly descriptive.
- Theme-based synthesis
- Group studies by theme/intervention/outcome (based on extraction fields). - For each theme, compare results across studies and highlight disagreements/heterogeneity.
- 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).
- 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.mdis traceable to specific fields/rows inpapers/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.