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WILLOSCAR

protocol-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: 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.).
    • 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.
  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).

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
LICENSE

ライセンスが設定されている

0/10
説明文

100文字以上の説明がある

+10
人気

GitHub Stars 100以上

0/15
最近の活動

1ヶ月以内に更新

+10
フォーク

10回以上フォークされている

+5
Issue管理

オープンIssueが50未満

+5
言語

プログラミング言語が設定されている

+5
タグ

1つ以上のタグが設定されている

+5

Reviews

💬

Reviews coming soon