protocol-writer

name

protocol-writer

description

Write a systematic review protocol into `output/PROTOCOL.md` (databases, queries, inclusion/exclusion, time window, extraction fields). **Trigger**: protocol, PRISMA, systematic review, inclusion/exclusion, 检索式, 纳入排除. **Use when**: systematic review pipeline 的起点（C1），需要先锁定 protocol 再开始 screening/extraction。 **Skip if**: 不是做 systematic review（或 protocol 已经锁定且不允许修改）。 **Network**: none. **Guardrail**: protocol 必须包含可执行的检索与筛选规则；需要 HUMAN 签字后才能进入 screening。

Protocol Writer (systematic review, PRISMA-style)

Goal: produce an executable protocol that a different reviewer could follow and reproduce.

Role cards (use explicitly)

Methodologist (protocol author)

Mission: make every rule operational so another person can reproduce the review.

Do:

• Define scope and RQs in testable language (what counts as in/out).
• Write copy/paste executable queries per source, including time window and search date.
• Specify screening labels and tie-break policy.
• Define an extraction schema with allowed values/units and how to record unknowns.

Avoid:

• Vague criteria ("relevant", "state-of-the-art", "high quality").
• Hidden degrees of freedom (unstated language limits, unstated time window).

Auditor (reproducibility checker)

Mission: remove ambiguity that would cause silent drift during screening/extraction.

Do:

• Add a short "decision log" section (what to record, where).
• Include a HUMAN approval gate statement before screening starts.

Avoid:

• Protocol prose that cannot be executed.

Role prompt: Systematic Review Protocol Author

You are writing a systematic review protocol that must be executable and auditable.

Your job is to define: scope, sources, queries, inclusion/exclusion, screening plan, extraction schema, and bias plan.

Constraints:
- rules must be operational (observable, testable)
- the protocol requires HUMAN approval before screening

Style:
- structured and concise
- avoid narrative filler; every paragraph should enable an action

Inputs

Required:

• STATUS.md (context + scope notes)

Optional:

• GOAL.md (topic phrasing)
• DECISIONS.md (any pre-agreed constraints)

Outputs

• output/PROTOCOL.md

Workflow

1. Scope + research questions

   • Translate the goal in GOAL.md (if present) into 1–3 review questions.
   • State what is in-scope / out-of-scope (keep consistent with STATUS.md).
   • If DECISIONS.md exists, treat it as authoritative for any pre-agreed constraints.

2. Sources

   • List databases/sources you will search (e.g., arXiv, ACL Anthology, IEEE Xplore, ACM DL, PubMed).
   • Specify any manual routes (snowballing: references/cited-by).

3. Search strategy (copy/paste executable)

   • For each source, write a concrete query string.
   • Define the time window (from/to year) and language constraints.
   • Record “search date” so the run is auditable.

4. Inclusion / exclusion criteria (operational, not vague)

   • Write MUST-HAVE criteria (study type, domain, outcomes).
   • Write MUST-NOT criteria (wrong population/task; non-peer-reviewed if excluded; etc.).
   • Assign stable IDs so screening can reference them:
     • Inclusion: I1, I2, ...
     • Exclusion: E1, E2, ...
   • Define how you handle duplicates and near-duplicates.

5. Screening plan

   • Define the screening stages (title/abstract → full text if applicable).
   • Define decision labels (at minimum include/exclude) and the tie-break policy.
   • Specify what gets recorded into papers/screening_log.csv.
   • Require that every screening decision cites at least one protocol clause ID (e.g., reason_codes=E3).

6. Extraction schema (downstream contract)

   • Define the columns that will appear in papers/extraction_table.csv.
   • Ensure every column has: definition, allowed values/units, and what counts as “unknown”.

7. Bias / risk-of-bias plan

   • Define the bias domains you will use (simple scales are OK).
   • Keep the rating scale consistent (recommended: low|unclear|high) and auditable.

8. Write output/PROTOCOL.md

   • Use clear headings; avoid prose that cannot be operationalized.
   • End with an explicit “HUMAN approval required before screening” note.

Mini examples (operational vs vague)

Inclusion criteria:

• Bad: Include papers that are relevant to LLM agents.
• Better: Include studies that evaluate an LLM-based agent in an interactive environment (tool use or embodied/web/OS), reporting at least one task success metric under a described protocol.

Exclusion criteria:

• Bad: Exclude low-quality papers.
• Better: Exclude non-empirical position papers; exclude studies without an evaluation protocol or without any quantitative/qualitative outcome reporting.

Query spec:

• Bad: "Search arXiv for agent papers"
• Better: provide an executable query string + fields (title/abstract) + time window + search date.

Definition of Done

• output/PROTOCOL.md includes: RQs, sources, executable queries, time window, inclusion/exclusion, screening plan, extraction schema, bias plan.
• A human can read output/PROTOCOL.md and run screening without asking “what do you mean by X?”.

Troubleshooting

Issue: queries are too broad / too narrow

Fix:

• Add exclusions for common false positives; add missing synonyms/acronyms; restrict fields (title/abstract) where supported.

Issue: screening/extraction criteria are vague (“relevant”, “state-of-the-art”)

Fix:

• Replace with observable rules (task/domain, metrics, dataset requirements, intervention/controls).