Agent skill

comm-lit-review

Communications-domain literature review and related-work search with database-aware source control. Use when the task is about communications, wireless, networking, satellite/NTN, Wi-Fi, cellular, transport protocols, congestion control, routing, scheduling, MAC/PHY, rate adaptation, channel estimation, beamforming, or communication-system research and the user wants papers, prior art, a survey, related work, or a landscape summary. Prioritize IEEE Xplore and ScienceDirect, prefer formal publications over preprints, and separate foundational work from recent progress.

Stars 6,306
Forks 582

Install this agent skill to your Project

npx add-skill https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/skills-codex/comm-lit-review

SKILL.md

Comm Lit Review

Overview

Run communications-focused paper search with tighter source policy than a generic literature review. Default to formal publications, prioritize IEEE Xplore and ScienceDirect, then ACM Digital Library, and output a review that is structured for research use rather than casual browsing.

Read references/source-policy.md before searching. Use references/domain-taxonomy.md to classify the topic, references/venue-tiering.md to rank venues, and references/output-template.md to format the final answer.

Workflow

1. Classify the request

Decide whether the request is primarily about:

  • Wireless PHY/MAC
  • Networking / transport / congestion control
  • Satellite / NTN / integrated space-air-ground systems
  • Cross-layer optimization / scheduling / resource allocation
  • Sensing / MEC / edge intelligence within communications systems

If the request is not clearly in communications systems research, fall back to a more general literature skill.

2. Lock the search policy

Apply these defaults unless the user overrides them:

  • Databases first: IEEE Xplore, ScienceDirect, then ACM Digital Library, then broader web
  • Publication bias: formal publications first, preprints second
  • Time window: cover both foundational and recent work
    • Default split: foundational before 2022, recent from 2022 onward
  • Output goal: research note, related-work summary, or comparison table rather than a raw search dump

If the user explicitly narrows scope, obey the narrower scope:

  • only journals
  • only IEEE / only ScienceDirect
  • only top venues
  • only LEO / only Wi-Fi / only transport
  • exclude arXiv
  • only papers after a certain year

3. Search primary sources first

Use a layered search strategy. For communications topics, do not build the review from random blog posts or derivative summaries.

Database ladder

Search in this order by default:

  1. ieeexplore.ieee.org
  2. sciencedirect.com
  3. dl.acm.org
  4. broader web using primary publisher pages, official conference sites, DOI pages, and author-hosted copies of already-identified formal papers

Only move to the next database tier when one of these is true:

  • the higher-priority tiers are too sparse for the topic
  • the topic is known to publish heavily outside the higher tier
  • the user explicitly asks for broader coverage

Venue ladder

Within each database tier, search venue tiers in this order:

  1. top communications and networking journals / top conferences
  2. mainstream strong journals / flagship broader conferences
  3. all remaining relevant formal venues

Follow the concrete tier lists in references/venue-tiering.md.

By default this venue tiering is a soft priority, not a hard whitelist.

  • Default behavior: start from Tier A, then widen if needed
  • If the user says only top venues, top journals only, top conferences only, or equivalent, switch to hard constraint mode and do not auto-expand beyond Tier A unless the user later relaxes the constraint

Use preprints only when:

  • the user explicitly asks for them
  • the area is very recent and formal versions are missing
  • a paper is clearly influential but only publicly accessible as a preprint

When a preprint is used, label it clearly as preprint.

4. Extract paper-level facts

For each relevant paper, capture:

  • Title
  • Authors
  • Year
  • Venue
  • Layer or system scope
  • Scenario and assumptions
  • Core method
  • Main result or claim
  • Limitation
  • Relevance to the user's topic
  • Source URL

Favor numbers, assumptions, and actual problem statements over generic summaries.

5. Synthesize as a communications review

Group papers by technical axis, not by search order. Common groupings:

  • PHY/MAC adaptation
  • Transport / congestion control
  • NTN / satellite resource management
  • Cross-layer or learning-based control
  • Measurement / empirical studies

Explicitly separate:

  • foundational vs recent papers
  • formal publications vs preprints
  • top-tier vs lower-tier venues when that distinction matters
  • single-link vs multi-user / network-wide formulations
  • simulation-only vs measurement / deployment-backed work

6. Produce a research-useful output

Follow the templates in references/output-template.md.

The default output should include:

  • a compact literature table
  • a short narrative on where the field stands
  • disagreements or unresolved assumptions
  • likely research gaps

Rules

  • Prefer primary sources over summaries or tertiary commentary.
  • Prefer IEEE and ScienceDirect first, ACM second, and only then broader web search unless the user asks otherwise.
  • Search venue tiers from top to broad within each database tier.
  • Treat venue tiers as soft ranking by default and hard constraint only when the user explicitly asks for top-only search.
  • Do not pretend a preprint is peer reviewed.
  • Do not collapse transport-layer rate control and PHY/MAC rate adaptation into one bucket without saying so explicitly.
  • If the topic spans multiple layers, say that the literature itself is split across layers.
  • If evidence is weak, say so instead of smoothing it over.

Expand your agent's capabilities with these related and highly-rated skills.

wanshuiyin/Auto-claude-code-research-in-sleep

ablation-planner

Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission. Codex designs ablations from a reviewer's perspective, CC reviews feasibility and implements.

6,306 582
Explore
wanshuiyin/Auto-claude-code-research-in-sleep

paper-plan

Generate a structured paper outline from review conclusions and experiment results. Use when user says "写大纲", "paper outline", "plan the paper", "论文规划", or wants to create a paper plan before writing.

6,306 582
Explore
wanshuiyin/Auto-claude-code-research-in-sleep

idea-discovery-robot

Workflow 1 adaptation for robotics and embodied AI. Orchestrates robotics-aware literature survey, idea generation, novelty check, and critical review to go from a broad robotics direction to benchmark-grounded, simulation-first ideas. Use when user says "robotics idea discovery", "机器人找idea", "embodied AI idea", "机器人方向探索", "sim2real 选题", or wants ideas for manipulation, locomotion, navigation, drones, humanoids, or general robot learning.

6,306 582
Explore
wanshuiyin/Auto-claude-code-research-in-sleep

training-check

Periodically check WandB metrics during training to catch problems early (NaN, loss divergence, idle GPUs). Avoids wasting GPU hours on broken runs. Use when training is running and you want automated health checks.

6,306 582
Explore
wanshuiyin/Auto-claude-code-research-in-sleep

paper-plan

Generate a structured paper outline from review conclusions and experiment results. Use when user says "写大纲", "paper outline", "plan the paper", "论文规划", or wants to create a paper plan before writing.

6,306 582
Explore
wanshuiyin/Auto-claude-code-research-in-sleep

idea-discovery-robot

Workflow 1 adaptation for robotics and embodied AI. Orchestrates robotics-aware literature survey, idea generation, novelty check, and critical review to go from a broad robotics direction to benchmark-grounded, simulation-first ideas. Use when user says \"robotics idea discovery\", \"机器人找idea\", \"embodied AI idea\", \"机器人方向探索\", \"sim2real 选题\", or wants ideas for manipulation, locomotion, navigation, drones, humanoids, or general robot learning.

6,306 582
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results