A skill your agent uses when deciding whether a data-management project belongs at ACM PODS (the database-theory symposium) or should be routed to SIGMOD/VLDB/ICDE (systems), ICDT (its sister theory…

MITAuto-check passed

Install Pods Topic Selection

skills CLI
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill pods-topic-selection -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills pods-topic-selection --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/PODS-Skills/skills/pods-topic-selection .claude/skills/pods-topic-selection && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
pods-topic-selection
GitHub stars
1.2k
Token cost
~1.5k tokens
SKILL.md length
675 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when deciding whether a data-management project belongs at ACM PODS (the database-theory symposium) or should be routed to SIGMOD/VLDB/ICDE (systems), ICDT (its sister theory…

  • Deciding whether a data-management project belongs at ACM PODS (the database-theory symposium)
  • SKILL.md covers The routing question that…, Sibling-venue routing table, Contribution shapes PODS rewards and The result-swap and re-label…, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Should be routed to SIGMOD/VLDB/ICDE (systems)

What it does

Pods Topic Selection is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when deciding whether a data-management project belongs at ACM PODS (the database-theory symposium) or should be routed to SIGMOD/VLDB/ICDE (systems), ICDT (its sister theory venue), LICS/ICALP/STOC (pure theory), or a journal (TODS/LMCS/JACM), by contribution shape, the result-swap test, and the PODS-vs-ICDT community fit.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. | 覆盖主流期刊的… The licence is MIT.

When your agent uses it

  • Deciding whether a data-management project belongs at ACM PODS (the database-theory symposium)
  • Should be routed to SIGMOD/VLDB/ICDE (systems)
  • ICDT (its sister theory venue)
  • LICS/ICALP/STOC (pure theory)

Example prompts

  • “/pods-topic-selection”

What it can do on your machine

Read from SKILL.md and the folder at commit 932eb23. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Pods Topic Selection loads about 1.5k tokens when it runs. Until then it costs about 88 tokens; SKILL.md has 675 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~88
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 675 words, ~1,537 tokens.

Download SKILL.mdSave it as .claude/skills/pods-topic-selection/SKILL.md (or your agent's skills folder).
name
pods-topic-selection
description
Use when deciding whether a data-management project belongs at ACM PODS (the database-theory symposium) or should be routed to SIGMOD/VLDB/ICDE (systems), ICDT (its sister theory venue), LICS/ICALP/STOC (pure theory), or a journal (TODS/LMCS/JACM), by contribution shape, the result-swap test, and the PODS-vs-ICDT community fit.

PODS Topic Selection

Decide the venue before drafting. PODS — the ACM SIGMOD/SIGACT Symposium on Principles of Database Systems — is the theoretical-foundations symposium held jointly with SIGMOD each year. Its papers are theorems about data management: models, query languages, complexity bounds, dichotomies, logic, and provably optimal algorithms. A technically strong paper whose real contribution is a faster system, a benchmark win, or an engineering artifact is respected and then rejected as out of scope — that paper is SIGMOD/VLDB/ICDE. PODS reviewers read for a provable, foundational statement about a cleanly defined model.

The routing question that matters most

The decisive question is rarely "is this about databases?" but "is the contribution a theorem or a system?" If the headline is a bound, a dichotomy, a semantics, an expressiveness result, or an algorithm with a matching lower bound, it is PODS-shaped. If the headline is throughput, latency, or accuracy on real workloads — even with clever theory inside — its home is a systems-DB flagship. PODS and SIGMOD share a week and a hallway but not a bar for acceptance.

Sibling-venue routing table

Signal in your projectBetter homeWhy
A bound, dichotomy, semantics, or provably optimal algorithm in a data modelPODSThe database-theory symposium; results are theorems with proofs
A system, index, or optimizer evaluated on real workloads for performanceSIGMOD / VLDB / ICDEThe systems-DB flagships; evidence is measured, not proved
Database theory, but you want the EDBT/ICDT federation or missed the PODS cycleICDTPODS's sister theory venue; overlapping community and reviewer pool, different calendar
Pure logic / finite model theory with no data-management payoffLICS / ICALP / STOC / FOCSTheory venues; PODS wants the data-management motivation to be central
A deep, long development beyond a 15-page symposium resultTODS / LMCS / JACM / VLDBJJournals with no symposium page ceiling; often the full-version home
Applied ML-for-data with empirical validation as the pointSIGMOD / VLDB / a ML venueNot a PODS theorem; route to where the evidence is measured

Contribution shapes PODS rewards

  • A new semantics or framework for an ill-defined problem — consistent query answering, provenance semirings, a data model for uncertainty — stated precisely and studied for decidability/complexity.
  • A complexity classification — a dichotomy (PTIME vs. hard), a fine-grained bound, a data-vs-combined-complexity separation over a query class.
  • An expressiveness or logic result — which logical language captures an operation (composition, view definition, path querying), with matching upper and lower bounds.
  • A provably optimal algorithm — a worst-case-optimal join, a constant-delay enumeration procedure, an MPC-round bound — the guarantee is a theorem, not a measured speedup.
  • Foundations of emerging data problems — differential privacy for queries, learning-theoretic guarantees for data tasks, graph-query theory — where PODS supplies the rigor.
Show full SKILL.md (239 more words)Show less

The result-swap and re-label tests

Two quick tests sharpen a borderline verdict:

  • Result-swap test: if you replaced your specific algorithm or construction with a different one, would a theorem still remain (a bound, a classification, an impossibility)? If not, the artifact is the contribution and a systems venue fits better.
  • Re-label test: could this paper be submitted to SIGMOD unchanged and read as native there? If its heart is a measured system with theory as garnish, route to SIGMOD/VLDB; if its heart is a proof, PODS is home. The mirror also holds for ICDT — if the paper is pure logic with no data-management question driving it, ICDT or LICS may fit better than PODS.

Maturity, without the ladder cliché

Fit is necessary but not sufficient. A conjecture with partial evidence but no proof is a workshop or a Gems-of-PODS talk, not a research paper; a theorem whose proof only handles a special case needs the general result or an honest scope; a sprawling development that cannot breathe in 15 pages plus appendix may belong in a journal first, with a PODS extended abstract of the core theorem. Submitting a half-proved result costs a full cycle even when the topic is perfect.

Cheap reconnaissance before committing

text
[Scope]     scan the last two PODS proceedings (dblp db/conf/pods, PACMMOD PODS track) for your
            subarea -> 3+ recent papers = a reviewer pool exists; 0 = mismatch or ICDT/LICS territory
[Citations] is your bibliography majority PODS/ICDT/LICS/TODS/JACM, or majority SIGMOD/VLDB?
            -> majority systems venues => reviewers may read you as a systems paper; reframe the intro
[Calendar]  PODS runs two cycles a year; compare the next PODS cycle with ICDT's and the systems
            deadlines, and route to the nearest honest fit rather than idling

Decision procedure

text
[Contribution] theorem (bound/dichotomy/semantics/optimal algorithm) or measured system?
[Model]        is there a cleanly defined data/query model the result is about?
[PODS vs ICDT] data-management theory with the SIGMOD community pull -> PODS; EDBT/ICDT federation
               fit or calendar -> ICDT
[Systems check] performance is the headline -> SIGMOD/VLDB/ICDE, not PODS
[Verdict]      PODS / ICDT / systems flagship / journal-first, with a one-line reason

Run this before the writing skills; a wrong venue decision wastes every later step. When the verdict is PODS, continue with pods-workflow for the two-cycle calendar and pods-writing-style for the paper shape.

© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in PODS-Skills/skills/pods-topic-selection of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

Compare with similar skills

Pods Topic Selection next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Pods Topic Selection this skillbrycewang-stanford/Awesome-Journal-Skills1.2k—~1.5kAutomated safety check: PassMIT
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Implementing Pod Security Admission Controllermukul975/Anthropic-Cybersecurity-Skills34k—~2.5kAutomated safety check: PassApache-2.0
TopicsZimoLiao/scholaraio577—~294Automated safety check: PassMIT
Topic Modelingbrycewang-stanford/Auto-Empirical-Research-Skills4.5k—~3.7kAutomated safety check: PassCustom licence
Bestblogs Topicginobefun/BestBlogs4k—~670Automated safety check: PassNone

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Questions about Pods Topic Selection

What does Pods Topic Selection do?

A skill your agent uses when deciding whether a data-management project belongs at ACM PODS (the database-theory symposium) or should be routed to SIGMOD/VLDB/ICDE (systems), ICDT (its sister theory…. Pods Topic Selection is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when deciding whether a data-management project belongs at ACM PODS (the database-theory symposium) or should be routed to SIGMOD/VLDB/ICDE (systems), ICDT (its sister theory venue), LICS/ICALP/STOC (pure theory), or a journal (TODS/LMCS/JACM), by contribution shape, the result-swap test, and the PODS-vs-ICDT community fit.

When should I use Pods Topic Selection?

Pods Topic Selection fits situations like: deciding whether a data-management project belongs at ACM PODS (the database-theory symposium); should be routed to SIGMOD/VLDB/ICDE (systems); ICDT (its sister theory venue); LICS/ICALP/STOC (pure theory).

How do I install Pods Topic Selection in Claude Code?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill pods-topic-selection -a claude-code`. Or copy the skill folder (PODS-Skills/skills/pods-topic-selection in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/pods-topic-selection in your project. Claude Code loads it when a task matches its description.

How do I install Pods Topic Selection in Codex?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill pods-topic-selection -a codex`. Or copy the skill folder (PODS-Skills/skills/pods-topic-selection in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/pods-topic-selection in your project. Codex loads it when a task matches its description.

Can I use Pods Topic Selection in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill pods-topic-selection -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/pods-topic-selection, .gemini/skills/pods-topic-selection, .github/skills/pods-topic-selection and .opencode/skills/pods-topic-selection in your project.

What does Pods Topic Selection need to run?

SKILL.md names no scripts, command-line tools or credentials: Pods Topic Selection is instructions for the agent only.

Does Pods Topic Selection access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Pods Topic Selection safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Pods Topic Selection use?

Pods Topic Selection is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Pods Topic Selection use?

About 1.5k tokens (SKILL.md is roughly 6.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Pods Topic Selection?

Skills that share tags, products or a category with Pods Topic Selection: Pod Sales (ruvnet/ruflo, 74k stars), Implementing Pod Security Admission Controller (mukul975/Anthropic-Cybersecurity-Skills, 34k stars), Topics (ZimoLiao/scholaraio, 577 stars) and Topic Modeling (brycewang-stanford/Auto-Empirical-Research-Skills, 4.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Pods Topic Selection?

brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,228 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.

Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.