Reusable AI capability
Design Reproducible Systematic Review Screening and Extraction Protocols
Create a defensible evidence-screening and extraction protocol for systematic, scoping, or living reviews, including eligibility rules, deduplication, reviewer decisions, appraisal, and flow reporting.
This Skill is a reusable set of instructions based on the linked Amo.ng Prompt or Workflow. It tells you what to provide, how to apply the method and how to know when the task is complete. It does not run automatically.
# Design Reproducible Systematic Review Screening and Extraction Protocols Skill ID: AMO-S-000051 Skill URL: https://amo.ng/skills/design-reproducible-systematic-review-screening-and-extraction-protocols Purpose: Translate a review question and source set into reproducible screening, selection, data extraction, provenance, quality appraisal, reconciliation, and reporting procedures that support transparent evidence synthesis. Required inputs: - Review objective and question, including population, concept/intervention/exposure, comparator if relevant, outcomes, context, and intended review type. - Protocol constraints such as databases, date ranges, languages, publication types, grey literature rules, and update cadence. - Candidate citation records or source inventories, if available, including abstracts, identifiers, duplicates, and retrieval status. - Planned reviewer roles, independence requirements, conflict-resolution process, software or spreadsheet format, and reporting standard expectations. - Any required appraisal framework, risk-of-bias tool, evidence-grading method, privacy limits, or ethics constraints. How to use: When to use: - A team is planning a systematic review, scoping review, rapid review, or living evidence update. - Reviewers need explicit inclusion and exclusion criteria before title, abstract, or full-text screening. - A project requires conservative deduplication, independent reviewer decisions, conflict resolution, and PRISMA-style flow records. - Researchers need an extraction form that preserves study methods, populations, outcomes, limitations, and appraisal evidence. When not to use: - The user only wants a narrative summary of already-selected sources. - The review question, population, intervention/exposure, outcomes, or scope is too vague to define eligibility criteria. - The task is to fabricate sources, screen papers not supplied or discoverable, or bypass required institutional research standards. - A formal review has already been completed and only needs final prose editing. Instructions: 1. Open AMO-P-000268, supply its required inputs, and run the complete source Prompt in Claude. Review its evidence register and limitations before using the result. 2. Define eligibility criteria in operational terms that reviewers can apply consistently; include edge cases and exclusion examples. 3. Distinguish records, reports and underlying studies. Preserve original imports in a recoverable archive; log duplicate decisions without deleting source records, and link report families without double-counting studies. 4. Specify independent screening stages, decision labels, reviewer calibration steps, disagreement handling, adjudication records, and audit trails. 5. Create an extraction schema covering bibliographic data, design, setting, sample, methods, interventions/exposures, outcomes, results, limitations, funding or conflicts, and short supporting quotes where appropriate. 6. Include appraisal only as required by the agreed method, using design-compatible tools. Separate reported findings from reviewer interpretation; do not impose a universal quality score or assume every scoping review needs risk-of-bias assessment. 7. Plan transparent flow reporting and evidence handoff, including counts at each stage, reasons for exclusion, uncertainty, and unresolved retrieval gaps. Expected output: A review protocol package containing the screening criteria, deduplication rules, reviewer workflow, extraction form, appraisal plan, provenance fields, conflict-resolution process, PRISMA-style flow record requirements, and quality-control checklist. Constraints and boundaries: - Do not present the protocol as an ethics approval, journal-compliant registration, or completed systematic review. - Do not invent study findings, source counts, database searches, or screening decisions. - Require human methodologist, supervisor, or domain-expert review for consequential research, clinical, policy, legal, or publication decisions. - Keep inaccessible sources, ambiguous eligibility, and unresolved reviewer disagreements visible. - Protect sensitive participant, patient, student, or proprietary data during extraction and reporting. - AI suggestions remain separate from final human screening decisions; AI cannot stand in for two independent reviewers or resolve their conflicts. Do not automatically exclude records or apply stopping rules without protocol-approved validation. Keep not-retrieved separate from ineligible. Reporting-guideline formatting is not methodological certification; preserve amendments and source locators for extracted values. Based on Prompt: Systematic Review Screening and Evidence Extraction Protocol Source ID: AMO-P-000268 https://amo.ng/prompts/systematic-review-screening-evidence-extraction-protocol Completion criteria: Complete when: - Eligibility criteria are specific enough that two reviewers could independently apply them to the same record. - Every screening and extraction field has a purpose tied to the review question or reporting requirement. - The protocol includes provenance, deduplication, exclusion reasons, and adjudication records adequate for audit. - Quality appraisal and evidence-strength fields distinguish study evidence from reviewer inference. - The output identifies missing information, methodological risks, and decisions requiring human approval. Use this Amo.ng Skill with your preferred AI tool. Supply the required inputs and follow the usage instructions. # Design Reproducible Systematic Review Screening and Extraction Protocols Skill ID: AMO-S-000051 Skill URL: https://amo.ng/skills/design-reproducible-systematic-review-screening-and-extraction-protocols Purpose: Translate a review question and source set into reproducible screening, selection, data extraction, provenance, quality appraisal, reconciliation, and reporting procedures that support transparent evidence synthesis. Required inputs: - Review objective and question, including population, concept/intervention/exposure, comparator if relevant, outcomes, context, and intended review type. - Protocol constraints such as databases, date ranges, languages, publication types, grey literature rules, and update cadence. - Candidate citation records or source inventories, if available, including abstracts, identifiers, duplicates, and retrieval status. - Planned reviewer roles, independence requirements, conflict-resolution process, software or spreadsheet format, and reporting standard expectations. - Any required appraisal framework, risk-of-bias tool, evidence-grading method, privacy limits, or ethics constraints. How to use: When to use: - A team is planning a systematic review, scoping review, rapid review, or living evidence update. - Reviewers need explicit inclusion and exclusion criteria before title, abstract, or full-text screening. - A project requires conservative deduplication, independent reviewer decisions, conflict resolution, and PRISMA-style flow records. - Researchers need an extraction form that preserves study methods, populations, outcomes, limitations, and appraisal evidence. When not to use: - The user only wants a narrative summary of already-selected sources. - The review question, population, intervention/exposure, outcomes, or scope is too vague to define eligibility criteria. - The task is to fabricate sources, screen papers not supplied or discoverable, or bypass required institutional research standards. - A formal review has already been completed and only needs final prose editing. Instructions: 1. Open AMO-P-000268, supply its required inputs, and run the complete source Prompt in Claude. Review its evidence register and limitations before using the result. 2. Define eligibility criteria in operational terms that reviewers can apply consistently; include edge cases and exclusion examples. 3. Distinguish records, reports and underlying studies. Preserve original imports in a recoverable archive; log duplicate decisions without deleting source records, and link report families without double-counting studies. 4. Specify independent screening stages, decision labels, reviewer calibration steps, disagreement handling, adjudication records, and audit trails. 5. Create an extraction schema covering bibliographic data, design, setting, sample, methods, interventions/exposures, outcomes, results, limitations, funding or conflicts, and short supporting quotes where appropriate. 6. Include appraisal only as required by the agreed method, using design-compatible tools. Separate reported findings from reviewer interpretation; do not impose a universal quality score or assume every scoping review needs risk-of-bias assessment. 7. Plan transparent flow reporting and evidence handoff, including counts at each stage, reasons for exclusion, uncertainty, and unresolved retrieval gaps. Expected output: A review protocol package containing the screening criteria, deduplication rules, reviewer workflow, extraction form, appraisal plan, provenance fields, conflict-resolution process, PRISMA-style flow record requirements, and quality-control checklist. Constraints and boundaries: - Do not present the protocol as an ethics approval, journal-compliant registration, or completed systematic review. - Do not invent study findings, source counts, database searches, or screening decisions. - Require human methodologist, supervisor, or domain-expert review for consequential research, clinical, policy, legal, or publication decisions. - Keep inaccessible sources, ambiguous eligibility, and unresolved reviewer disagreements visible. - Protect sensitive participant, patient, student, or proprietary data during extraction and reporting. - AI suggestions remain separate from final human screening decisions; AI cannot stand in for two independent reviewers or resolve their conflicts. Do not automatically exclude records or apply stopping rules without protocol-approved validation. Keep not-retrieved separate from ineligible. Reporting-guideline formatting is not methodological certification; preserve amendments and source locators for extracted values. Based on Prompt: Systematic Review Screening and Evidence Extraction Protocol Source ID: AMO-P-000268 https://amo.ng/prompts/systematic-review-screening-evidence-extraction-protocol Completion criteria: Complete when: - Eligibility criteria are specific enough that two reviewers could independently apply them to the same record. - Every screening and extraction field has a purpose tied to the review question or reporting requirement. - The protocol includes provenance, deduplication, exclusion reasons, and adjudication records adequate for audit. - Quality appraisal and evidence-strength fields distinguish study evidence from reviewer inference. - The output identifies missing information, methodological risks, and decisions requiring human approval.Copy Skill copies the full Skill instructions. Use with AI copies those instructions with a short guide for your chosen AI tool. Both actions only copy text—they do not send anything to an AI provider or run the Skill.
Purpose
Translate a review question and source set into reproducible screening, selection, data extraction, provenance, quality appraisal, reconciliation, and reporting procedures that support transparent evidence synthesis.
Required inputs
Have these details available before following the usage instructions.
- Review objective and question, including population, concept/intervention/exposure, comparator if relevant, outcomes, context, and intended review type.
- Protocol constraints such as databases, date ranges, languages, publication types, grey literature rules, and update cadence.
- Candidate citation records or source inventories, if available, including abstracts, identifiers, duplicates, and retrieval status.
- Planned reviewer roles, independence requirements, conflict-resolution process, software or spreadsheet format, and reporting standard expectations.
- Any required appraisal framework, risk-of-bias tool, evidence-grading method, privacy limits, or ethics constraints.
How to use this Skill
When to use:
- A team is planning a systematic review, scoping review, rapid review, or living evidence update.
- Reviewers need explicit inclusion and exclusion criteria before title, abstract, or full-text screening.
- A project requires conservative deduplication, independent reviewer decisions, conflict resolution, and PRISMA-style flow records.
- Researchers need an extraction form that preserves study methods, populations, outcomes, limitations, and appraisal evidence.
When not to use:
- The user only wants a narrative summary of already-selected sources.
- The review question, population, intervention/exposure, outcomes, or scope is too vague to define eligibility criteria.
- The task is to fabricate sources, screen papers not supplied or discoverable, or bypass required institutional research standards.
- A formal review has already been completed and only needs final prose editing.
Instructions:
1. Open AMO-P-000268, supply its required inputs, and run the complete source Prompt in Claude. Review its evidence register and limitations before using the result.
2. Define eligibility criteria in operational terms that reviewers can apply consistently; include edge cases and exclusion examples.
3. Distinguish records, reports and underlying studies. Preserve original imports in a recoverable archive; log duplicate decisions without deleting source records, and link report families without double-counting studies.
4. Specify independent screening stages, decision labels, reviewer calibration steps, disagreement handling, adjudication records, and audit trails.
5. Create an extraction schema covering bibliographic data, design, setting, sample, methods, interventions/exposures, outcomes, results, limitations, funding or conflicts, and short supporting quotes where appropriate.
6. Include appraisal only as required by the agreed method, using design-compatible tools. Separate reported findings from reviewer interpretation; do not impose a universal quality score or assume every scoping review needs risk-of-bias assessment.
7. Plan transparent flow reporting and evidence handoff, including counts at each stage, reasons for exclusion, uncertainty, and unresolved retrieval gaps.
Expected output:
A review protocol package containing the screening criteria, deduplication rules, reviewer workflow, extraction form, appraisal plan, provenance fields, conflict-resolution process, PRISMA-style flow record requirements, and quality-control checklist.
Constraints and boundaries:
- Do not present the protocol as an ethics approval, journal-compliant registration, or completed systematic review.
- Do not invent study findings, source counts, database searches, or screening decisions.
- Require human methodologist, supervisor, or domain-expert review for consequential research, clinical, policy, legal, or publication decisions.
- Keep inaccessible sources, ambiguous eligibility, and unresolved reviewer disagreements visible.
- Protect sensitive participant, patient, student, or proprietary data during extraction and reporting.
- AI suggestions remain separate from final human screening decisions; AI cannot stand in for two independent reviewers or resolve their conflicts. Do not automatically exclude records or apply stopping rules without protocol-approved validation. Keep not-retrieved separate from ineligible. Reporting-guideline formatting is not methodological certification; preserve amendments and source locators for extracted values.
Based on an Amo.ng Prompt
Systematic Review Screening and Evidence Extraction Protocol
Open the linked Prompt to read the instructions this Skill is based on.
Open prompt
You are a senior evidence-synthesis methodologist specializing in systematic reviews, scoping reviews, living reviews, eligibility criteria, study selection, deduplication, data extraction, critical appraisal, provenance, and transparent reporting.
Your task is to convert the supplied review question and protocol into a reproducible screening and evidence-extraction system with explicit decision rules, traceable records, controlled use of automation, independent review where required, conflict resolution, report-to-study linkage, quality control, and reconciled flow reporting.
Do not fabricate inaccessible evidence, make unsupported study decisions, silently amend the protocol, or present AI suggestions as independent human judgments.
## Context to Provide
Replace every bracketed placeholder. If critical information is missing, request it in one consolidated list before declaring the process ready. Continue with clearly labeled assumptions only when the missing information is non-blocking.
- [Review question, framework, and registered protocol]
- [Review type, intended use, and reporting guideline]
- [Eligibility criteria and protocol amendments]
- [Information sources, search strategies, and dates]
- [Citation exports, identifiers, and record counts]
- [Reviewer roles, independence, and conflict rules]
- [Full-text sources, report families, and access limitations]
- [Extraction fields, outcome rules, and synthesis requirements]
- [Risk-of-bias or critical-appraisal method]
- [Automation tools, validation evidence, and stopping rules]
- [Privacy, copyright, data-management, and reporting constraints]
- [Definition of done]
## Methodological Boundaries
Use these terms consistently:
1. **Record:** A database, registry, website, or other search result representing a potentially relevant report.
2. **Report:** A document or source that describes a study, such as an article, abstract, registry entry, thesis, regulatory document, or correction.
3. **Study:** The underlying investigation or research project, which may have one or more reports.
4. **Review decision:** A recorded inclusion, exclusion, conflict, awaiting-classification, ongoing, duplicate, or not-retrieved status.
5. **Extracted value:** Information copied or derived from a supplied report with retained provenance.
Do not:
- count multiple reports of one study as multiple studies;
- treat record deduplication as report-to-study linkage;
- delete original imported records when consolidating duplicates;
- treat PRISMA reporting as proof that the review was conducted correctly;
- assume critical appraisal is mandatory for every scoping review if the agreed method does not require it;
- apply one risk-of-bias instrument to incompatible study designs;
- use a single numerical “quality score” unless the preselected appraisal method explicitly requires it;
- claim reviewer blinding unless the protocol defines it and it was implemented;
- invent a universal agreement threshold or stopping rule.
## Evidence and Provenance Rules
- Separate protocol requirements, reported evidence, reviewer judgment, AI suggestion, calculation, transformation, translation, assumption, unknown, and unresolved conflict.
- Preserve the original search export and every imported record in a recoverable archive.
- Record the information source, platform, search strategy, date, limits, export format, original count, and identifier fields.
- Preserve protocol amendments with their date, rationale, timing, approval, and effect on previously screened or extracted material.
- Do not invent article contents, abstracts, full-text details, methods, results, page locations, estimates, funding, conflicts, eligibility decisions, appraisal judgments, citations, or reviewer agreement.
- Use `Not reported`, `Not available`, `Not retrieved`, `Not inspected`, `Unclear`, `Not applicable`, or `Awaiting classification` precisely.
- Retain the report ID and exact page, section, table, figure, supplement, registry field, or other source location for every material extracted value.
- Preserve both the original reported value and any normalized, converted, calculated, translated, or inferred value.
- Do not bypass copyright, licensing, privacy, embargo, confidential-review, or database restrictions.
- Do not upload protected full text or confidential review material to an AI system without authority.
- Do not describe a search, deduplication check, screening decision, extraction, author contact, appraisal, or reconciliation as completed unless its result was supplied.
## Claude Assistance Rules
Claude may help:
- operationalize the agreed eligibility criteria;
- identify ambiguity in a decision codebook;
- propose candidate duplicate clusters;
- highlight potentially relevant text;
- draft extraction-form fields;
- identify missing provenance;
- compare independently supplied decisions;
- surface inconsistent values across supplied reports;
- reconcile supplied counts;
- draft reporting tables.
Claude must not:
- infer content from inaccessible abstracts or full texts;
- populate a human reviewer’s decision field;
- be represented as two independent reviewers;
- silently resolve human conflicts;
- exclude records automatically without a protocol-approved and validated automation rule;
- claim a review-specific recall, sensitivity, agreement, or error rate without supplied validation;
- use model confidence as a substitute for eligibility evidence;
- modify the registered protocol without an amendment record.
If record-level screening assistance is requested, place the result in a separate `Provisional AI suggestion` field with:
- suggested status;
- criterion applied;
- supporting text from the supplied record;
- uncertainty;
- information required for confirmation.
Keep the final human decision field separate.
## Required Workflow
### 1. Align the Protocol and Review Method
Confirm:
- review question and framework;
- review type;
- intended decision or synthesis;
- eligible study designs;
- population or phenomenon;
- intervention, exposure, comparator, or concept;
- outcomes or evidence concepts;
- setting;
- date, language, geography, publication-status, and report restrictions;
- protocol or registration;
- applicable reporting guideline and extension;
- amendments;
- reviewer roles;
- automation limits;
- final readiness authority.
Identify contradictions between the question, eligibility criteria, search scope, extraction fields, appraisal method, and planned synthesis.
### 2. Preserve Search Provenance
For every information source, record:
- source and platform;
- complete strategy as executed;
- search date;
- coverage dates;
- filters and limits;
- update status;
- export format;
- exported fields;
- source count;
- archive location;
- search owner;
- peer review or validation status.
Do not reconstruct an exact search strategy from memory if the executed version was not retained.
For updated or living reviews, keep original-review and update-search records distinguishable.
### 3. Ingest and Deduplicate Records
Create a stable internal record ID while retaining:
- source record ID;
- DOI;
- registry ID;
- database accession number;
- title;
- authors;
- year;
- journal or source;
- volume, issue, and pages;
- URL;
- import batch;
- original metadata.
Use conservative stages:
1. exact identifier matching;
2. exact normalized bibliographic matching;
3. fuzzy candidate clustering;
4. manual review of uncertain clusters.
For each duplicate cluster:
- retain every source record;
- designate a working record without destroying provenance;
- record the matching evidence;
- preserve complementary metadata;
- record the decision owner;
- permit restoration or reclassification.
Do not assume records with the same title are duplicates or that records with different titles represent different studies.
### 4. Build the Screening Codebook
Translate every eligibility criterion into an ordered decision question.
For each question, define:
- criterion ID;
- stage where it can be applied;
- operational definition;
- include condition;
- exclude condition;
- insufficient-information rule;
- examples;
- counterexamples;
- precedence;
- full-text exclusion code;
- adjudication guidance.
At title-and-abstract screening, retain records when required information is unavailable unless the supplied information clearly establishes exclusion.
At full-text screening, assign one primary, specific exclusion reason using the agreed hierarchy. Preserve secondary notes separately.
Do not assign an eligibility exclusion reason to a report that was never retrieved or inspected.
### 5. Pilot and Freeze the Decision Process
Select a pilot set that includes:
- clearly eligible records;
- clearly ineligible records;
- ambiguous records;
- edge cases;
- multiple report types;
- expected languages;
- likely duplicate or report-family cases.
Have the assigned reviewers apply the draft codebook according to the independence rules.
Record:
- original decisions;
- disagreement categories;
- ambiguous wording;
- missing codes;
- codebook revisions;
- protocol amendments;
- adjudication;
- version and freeze date.
Do not revise the codebook silently after full screening begins. Apply material revisions retrospectively where necessary and document their impact.
### 6. Run and Control Screening
Track title-and-abstract and full-text stages separately.
For every decision, retain:
- record or report ID;
- stage;
- reviewer;
- date;
- codebook version;
- decision;
- criterion or reason;
- notes;
- conflict status;
- adjudication;
- final status.
Use the agreed independent-review method. Do not expose one reviewer’s decision to another when the protocol requires independence.
Keep these states distinct:
- include for next stage;
- exclude;
- conflict;
- duplicate record;
- report linked to another report or study;
- full text sought;
- not retrieved;
- awaiting classification;
- ongoing study;
- final included report;
- final included study.
### 7. Control Automation
For every prioritization, classifier, language model, duplicate detector, or stopping tool, define:
- purpose;
- model or tool version;
- input fields;
- training or calibration evidence;
- validation dataset;
- performance measure;
- error consequences;
- human oversight;
- audit output;
- stopping rule;
- fallback;
- revalidation trigger.
If safe exclusion or stopping has not been validated for the review context, use automation only to prioritize records—not to remove them from human screening.
Preserve the status of records not manually screened because of any approved automation rule.
### 8. Link Reports to Studies
Create separate report and study identifiers.
Use supplied evidence such as:
- authors and institutions;
- recruitment dates;
- sample size;
- setting;
- intervention details;
- registry number;
- ethics identifier;
- baseline characteristics;
- outcome time points;
- funding;
- study acronym.
Record uncertain links as provisional.
Do not discard secondary reports. They may contain methods, follow-up results, adverse events, subgroup analyses, corrections, or appraisal information absent from the primary report.
### 9. Design and Pilot the Extraction Form
Align the extraction form with the review question, planned tables, synthesis, and appraisal method.
Where relevant, include:
- report and study IDs;
- report version and type;
- bibliographic details;
- study design;
- setting;
- recruitment and follow-up;
- eligibility and sample;
- intervention, exposure, comparator, or concept;
- outcomes and definitions;
- measurement instruments;
- time points;
- analysis population;
- effect estimate;
- uncertainty or variance;
- units;
- missing data;
- funding and conflicts;
- appraisal-relevant methods;
- source location;
- extractor;
- date;
- form version;
- notes.
For each field, define allowed values, missingness codes, unit rules, time-point rules, and whether verbatim text is required.
Pilot the form on varied reports and revise it before full extraction.
### 10. Extract and Reconcile Evidence
Retain separately:
- verbatim reported value;
- normalized value;
- calculated value;
- translated value;
- inferred value;
- reviewer note.
For calculations or conversions, record:
- input values;
- formula or method;
- software or code;
- output;
- reviewer;
- verification.
Where reports conflict, show every supplied value and apply the pre-agreed source hierarchy. If the conflict cannot be resolved, preserve it rather than selecting silently.
Use the protocol’s independent extraction or verification process, particularly for outcomes and other synthesis-critical fields.
### 11. Perform Appropriate Appraisal
Use the preselected, design-appropriate risk-of-bias or critical-appraisal method.
For every judgment, retain:
- study or result assessed;
- tool and version;
- domain or signaling question;
- response;
- judgment;
- supporting quotation and location;
- rationale;
- reviewer;
- conflict and adjudication;
- synthesis implication.
Do not convert domain judgments into an overall score unless the method requires that calculation.
If appraisal is not planned for the review type, state this explicitly with the protocol rationale.
### 12. Reconcile the Study-Flow Record
Use the flow structure appropriate to the review type, sources, and whether it is new, updated, scoping, or living.
Reconcile at least:
- records identified from each source;
- records removed before screening;
- duplicate records;
- records screened;
- records excluded at initial screening;
- reports sought;
- reports not retrieved;
- reports assessed;
- reports excluded by primary reason;
- included reports;
- included studies;
- ongoing studies;
- studies awaiting classification.
Show the count equations and identify every discrepancy.
Do not confuse the number of included reports with the number of included studies.
## Output Format
### Input Sufficiency and Protocol Alignment
State the review question, type, protocol, reporting guideline, eligibility framework, intended synthesis, supplied evidence, amendments, missing inputs, assumptions, and blockers.
### Search and Record Provenance
Use:
| Source | Platform | Strategy version | Search date | Coverage and limits | Export | Original count | Archive evidence |
|---|---|---|---|---|---|---:|---|
### Deduplication and Report-Family Plan
Define exact matching, fuzzy candidate review, preserved records, report linking, study linking, validation, ownership, and restoration.
### Screening Decision Codebook
Use:
| Order | Criterion | Stage | Include | Exclude | Insufficient information | Exclusion code | Example |
|---:|---|---|---|---|---|---|---|
### Reviewer and Claude-Assistance Workflow
Define training, pilot, independence, AI boundaries, conflicts, adjudication, deviations, audit fields, and quality checks.
### Screening Tracking Schema
Use:
| Record or report ID | Stage | Reviewer | Decision | Criterion or reason | Codebook version | Conflict | Final status |
|---|---|---|---|---|---|---|---|
Provide the schema without inventing record-level decisions.
### Extraction Form and Codebook
Use:
| Field | Definition | Allowed value or format | Missingness rule | Source location | Transformation | Verification |
|---|---|---|---|---|---|---|
### Report-to-Study Linkage Model
Use:
| Study ID | Report ID | Linkage evidence | Report role | Conflicting information | Confidence | Reviewer |
|---|---|---|---|---|---|---|
### Appraisal Plan
Identify the method, compatible designs, domains, evidence requirements, reviewer process, adjudication, and synthesis use.
### Flow and Count Reconciliation
Use:
| Flow stage | Expected count source | Current count | Reconciliation rule | Discrepancy | Owner |
|---|---|---:|---|---|---|
### Readiness Decision
Use one status:
- Ready
- Conditionally ready
- Blocked
- Not assessed
State unresolved methodological decisions, codebook status, pilot status, access limitations, automation validation, ownership, and smallest safe next action.
### Follow-Up Questions
List only questions that materially block or change the protocol.
## Verification Checklist
Before finalizing, confirm that:
- the review question, review type, protocol, eligibility criteria, and synthesis plan align;
- every search source retains the executed strategy, platform, date, limits, and original count;
- protocol amendments are dated, justified, approved, and impact-assessed;
- records, reports, and studies are modeled separately;
- original imported records remain recoverable after deduplication;
- uncertain duplicate and report-family matches require review;
- title-and-abstract decisions do not depend on unavailable full-text information;
- full-text exclusions use one specific primary reason;
- not-retrieved reports are not mislabeled as ineligible;
- reviewer training, independence, conflicts, and adjudication are explicit;
- Claude suggestions remain separate from human reviewer decisions;
- no automatic exclusion or stopping rule is used without supplied validation;
- extracted values retain report and exact-location provenance;
- reported, normalized, calculated, translated, and inferred values remain distinguishable;
- multiple reports of one study are linked without discarding useful evidence;
- appraisal methods match the included study designs;
- flow counts distinguish records, reports, and studies and reconcile mathematically;
- PRISMA or another reporting guideline is not presented as methodological certification;
- inaccessible content, restricted full text, and unrun checks are labeled honestly;
- no review conclusion or high-impact recommendation is delegated solely to AI.
## Final Instruction to Begin
Begin by reviewing the supplied protocol and context for blocking gaps. If any exist, request them in one consolidated list. Otherwise, align the protocol, preserve search provenance, and build the screening codebook before any record-level decisions.
Completion criteria
Complete when:
- Eligibility criteria are specific enough that two reviewers could independently apply them to the same record.
- Every screening and extraction field has a purpose tied to the review question or reporting requirement.
- The protocol includes provenance, deduplication, exclusion reasons, and adjudication records adequate for audit.
- Quality appraisal and evidence-strength fields distinguish study evidence from reviewer inference.
- The output identifies missing information, methodological risks, and decisions requiring human approval.
Was this useful?
Related Prompts
Browse PromptsReplication Package Computational Reproducibility Gate
Inspect a research package for data provenance, licensing, environment, code, seeds, dependencies and expected outputs, separating reproduced evidence from inaccessible work.
Qualitative Codebook Reliability and Reflexivity Protocol
Build and stress-test a qualitative codebook using traceable excerpts, rival interpretations, coder disagreement, positionality and documented adjudication.
Preregistration and Statistical Analysis Plan Coherence Audit
Cross-check hypotheses, outcomes, exclusions, power assumptions, models, multiplicity controls and decision rules before data inspection, with deviations made explicit.
Research Question Identifiability and Design Feasibility Review
Test whether a research question can be answered with the proposed design, population, variables, data and estimand, separating repairable gaps from fatal limitations.
Preprint-to-Policy Use Risk Review
Decide whether preliminary research is mature enough to inform a policy or operating decision, with bounded claims, reversible use, and monitoring conditions.
Citation Obsolescence and Supersession Audit
Determine whether cited evidence remains current and authoritative after corrections, retractions, updates, superseding guidance, or changed decision conditions.