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Agent skill · Audited from source

systematic-literature-review

skill · bytedance/deer-flowMIT licenceAudited 31 Oct 2026 · source 56da65e1a2a6

★ 84,768pushed today
✓SAFEGrade B · 89/100 · 31 Oct 2026 · 56da65e
84,768repo stars · whole bytedance/deer-flow

Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit 56da65e1a2a6 and observed network access and no hard-coded secrets. What it does: Use this skill when the user wants a systematic literature review, survey, or synthesis across multiple academic papers on a topic. Also covers annotated bibliographies and cross-paper comparisons. Searches arXiv and…

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Cite this page

ModelsAtlas. “systematic-literature-review (bytedance/deer-flow)”. Retrieved 31 Oct 2026. https://modelsatlas.com/skills/bytedance/systematic-literature-review

Trust audit

Audit 0.4.1 · source read 31 Oct 2026

Trust score89/100✓SAFE B
0 critical0 high0 medium0 low0 info

SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 16,667 of 17,602 audited skills.

What the source does

  • FilesystemNone observedNo reads or writes in the source
  • NetworkDeclared4 observations
  • ShellNone observedNo commands run in the source
  • DependenciesPinnedNothing floats
  • SecretsNone foundNo keys in source

Five audit layers

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityPASS0
L1 Static sourceSecrets, path traversal, supply chain, hidden codePASS0
L2 InstructionsPrompt injection, authority framing, hidden directivesPASS0
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: no behavioural pass.

Findings (0)

No findings at any severity. We re-audit when the source changes.

Audit 0.4.1 · source sha 56da65e1a2a6 · 31 Oct 2026Report an issue or request a re-scan

Provenance

Who published it, and what the verdict is pinned to

  • Publisherbytedance GitHub organizationOwner of the repository this skill is read from
  • Source folderbytedance/deer-flow/skills/public/systematic-literature-reviewThe exact folder we audited
  • LicenceMITAs the repository states it
  • Commit pinned for this verdict56da65e1a2a6A new audit runs when the source changes
  • Repository statusNot archivedPushed today
  • Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

What it tells the agent

Full source on GitHub ↗

Its description: Use this skill when the user wants a systematic literature review, survey, or synthesis across multiple academic papers on a topic. Also covers annotated bibliographies and cross-paper comparisons. Searches arXiv and…

---
name: systematic-literature-review
description: Use this skill when the user wants a systematic literature review, survey, or synthesis across multiple academic papers on a topic. Also covers annotated bibliographies and cross-paper comparisons. Searches arXiv and outputs reports in APA, IEEE, or BibTeX format. Not for single-paper tasks — use academic-paper-review for reviewing one paper.
---

# Systematic Literature Review Skill

## Overview

This skill produces a structured **systematic literature review (SLR)** across multiple academic papers on a research topic. Given a topic query, it searches arXiv, extracts structured metadata (research question, methodology, key findings, limitations) from each paper in parallel, synthesizes themes across the full set, and emits a final report with consistent citations.

**Distinct from `academic-paper-review`:** that skill does deep peer review of a single paper. This skill does breadth-first synthesis across many papers. If the user hands you one paper URL and asks "review this paper", route to `academic-paper-review` instead.

## When to Use This Skill

Use this skill when the user wants any of the following:

- A literature survey on a topic ("survey transformer attention variants", "review the literature on diffusion models")
- A synthesis across multiple papers ("what do recent papers say about X", "compare methodologies across papers on Y")
- A systematic review with consistent citation format ("do an SLR on Z in APA format")
- An annotated bibliography on a topic
- An overview of research trends in a field over a time window

Do **not** use this skill when:

- The user provides exactly one paper and asks to review it (use `academic-paper-review`)
- The user asks a factual question that does not require synthesizing multiple sources (answer directly)
- The user wants general web research without academic rigor (use standard web search)

## Workflow

The workflow has five phases. Follow them in order.

### Phase 1: Plan

Before doing any retrieval, confirm the following with the user. If any of these are unclear, ask **one** clarifying question that covers the missing pieces. Do not ask one question at a time.

- **Topic**: the research area in plain English (e.g. "transformer attention variants").
- **Scope**: how many papers (default 20, hard upper bound 50), optional time window (e.g. "last 2 years"), optional arXiv category (e.g. `cs.CL`, `cs.CV`).
- **Citation format**: APA, IEEE, or BibTeX (default APA if the user does not specify and does not seem to be writing for a specific venue).
- **Output location**: where to save the final report (default `/mnt/user-data/outputs/`).

If the user says "50+ papers", politely cap it at 50 and explain that synthesis quality degrades quickly past that — for larger surveys they should split by sub-topic.

### Phase 2: Search arXiv

Call the bundled search script. Do **not** try to scrape arXiv by other means and do **not** write your own HTTP client — this script handles URL encoding, Atom XML parsing, and id normalization correctly.

```bash
python /mnt/skills/public/systematic-literature-review/scripts/arxiv_search.py \
  "<topic>" \
  --max-results <N> \
  [--category <cat>] \
  [--sort-by relevance] \
  [--start-date YYYY-MM-DD] \
  [--end-date YYYY-MM-DD]
```

**IMPORTANT — extract 2-3 core keywords before searching.** Do not pass the user's full topic description as the query. Before calling the script, mentally reduce the topic to its 2-3 most essential terms. Drop qualifiers like "in computer vision", "for NLP", "variants", "recent" — those belong in `--category` or `--start-date`, not in the query string.

**Query phrasing — keep it short.** The script wraps multi-word queries in double quotes for phrase matching on arXiv. This means:

- `"diffusion models"` → searches for the exact phrase → good, returns relevant papers.
- `"diffusion models in computer vision"` → searches for that exact 5-word phrase → **too specific, likely returns 0 results** because few papers contain that exact string.

Use **2-3 core keywords** as the query, and use `--category` to narrow the field instead of stuffing field names into the query. Examples:

| User says | Good query | Bad query |
|---|---|---|
| "diffusion models in computer vision" | `"diffusion models" --category cs.CV` | `"diffusion models in computer vision"` |
| "transformer attention variants" | `"transformer attention"` | `"transformer attention variants in NLP"` |
| "graph neural networks for molecules" | `"graph neural networks" --category cs.LG` | `"graph neural networks for molecular property prediction"` |

The script prints a JSON array to stdout. Each paper has: `id`, `title`, `authors`, `abstract`, `published`, `updated`, `categories`, `pdf_url`, `abs_url`.

**Sort strategy**:

- **Always use `relevance` sorting** — arXiv's BM25-style scoring ensures results are actually about the user's topic. `submittedDate` sorting returns the most recently submitted papers in the category regardless of topic relevance, which produces mostly off-topic results.
- When the user asks for "recent" papers or gives a time window, use `--sort-by relevance` **combined with `--start-date`** to constrain the time range while keeping results on-topic. For example, "recent diffusion model papers" → `--sort-by relevance --start-date 2024-01-01`, not `--sort-by submittedDate`.
- `submittedDate` sorting is only appropriate when the user explicitly asks for chronological order (e.g. "show me papers in the order they were published"). This is rare.
- `lastUpdatedDate` is rarely useful; ignore it unless the user asks.

**Run the search exactly once.** Do not retry with modified queries if the results seem imperfect — arXiv's relevance ranking is what it is. Retrying with different query phrasings wastes tool calls and risks hitting the recursion limit. If the results are genuinely empty (0 papers), tell the user and suggest they broaden their topic or remove the c

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

Install

Pinned to the audited commit 56da65e

Download folder ↗
git clone https://github.com/bytedance/deer-flow
git -C deer-flow checkout 56da65e1a2a6

The author documents no install command, so this uses the repository directly. Our verdict covers commit 56da65e1a2a6 only.

Works in

The author has not said which agents this skill supports, and we have not tested it in any.

Audit history

Every audit, every source change

  1. ✓SAFE B 89 / 100

    first audit · source 56da65e1a2a6

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Questions about systematic-literature-review

What does the systematic-literature-review skill do?
An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours.
Is systematic-literature-review safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can systematic-literature-review access on my machine?
The audit observed that it reaches the network. Each of those is consistent with what it says it does. Secrets in the source: none found.
How current is this page?
The grade is for one exact copy of the source (56da65e1a2a6), read on 2026-10-31. The repository is watched, and a new audit runs when it changes — this is the first audit.

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