Digital Forensics
sickn33/agentic-awesome-skills
Authorized digital forensics: memory dumps, disk timelines, PCAP investigation, artifact triage, and incident-response evidence preservation.
A skill your agent uses when an accepted SIGIR paper must become the ACM Digital Library version of record — de-anonymizing the sigconf source, CCS concepts and keywords, the e-rights form, TAPS…
MITAuto-check passed
Install Sigir Camera Ready
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigir-camera-ready -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills sigir-camera-ready --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/SIGIR-Skills/skills/sigir-camera-ready .claude/skills/sigir-camera-ready && rm -rf skills-srcUse ~/.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/
Install the "sigir-camera-ready" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGIR-Skills/skills/sigir-camera-ready into .claude/skills/sigir-camera-ready/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigir-camera-ready", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGIR-Skills/skills/sigir-camera-readyType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigir-camera-ready -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills sigir-camera-ready --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/SIGIR-Skills/skills/sigir-camera-ready .agents/skills/sigir-camera-ready && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "sigir-camera-ready" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGIR-Skills/skills/sigir-camera-ready into .agents/skills/sigir-camera-ready/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigir-camera-ready", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigir-camera-ready -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills sigir-camera-ready --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/SIGIR-Skills/skills/sigir-camera-ready .cursor/skills/sigir-camera-ready && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "sigir-camera-ready" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGIR-Skills/skills/sigir-camera-ready into .cursor/skills/sigir-camera-ready/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigir-camera-ready", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/brycewang-stanford/Awesome-Journal-Skills.git --path SIGIR-Skills/skills/sigir-camera-ready--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigir-camera-ready -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills sigir-camera-ready --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/SIGIR-Skills/skills/sigir-camera-ready .gemini/skills/sigir-camera-ready && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "sigir-camera-ready" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGIR-Skills/skills/sigir-camera-ready into .gemini/skills/sigir-camera-ready/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigir-camera-ready", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills sigir-camera-readyInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigir-camera-ready -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/SIGIR-Skills/skills/sigir-camera-ready .github/skills/sigir-camera-ready && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "sigir-camera-ready" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGIR-Skills/skills/sigir-camera-ready into .github/skills/sigir-camera-ready/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigir-camera-ready", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigir-camera-ready -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills sigir-camera-ready --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/SIGIR-Skills/skills/sigir-camera-ready .opencode/skills/sigir-camera-ready && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "sigir-camera-ready" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGIR-Skills/skills/sigir-camera-ready into .opencode/skills/sigir-camera-ready/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigir-camera-ready", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
sigir-camera-ready- GitHub stars
- 1.2k
- Token cost
- ~1.7k tokens
- SKILL.md length
- 815 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when an accepted SIGIR paper must become the ACM Digital Library version of record — de-anonymizing the sigconf source, CCS concepts and keywords, the e-rights form, TAPS…
- Works in 3 steps: e-rights: the contact author receives… → TAPS upload: zip your LaTeX (or Word)… → Proofs: check both renderings. Tables…
- An accepted SIGIR paper must become the ACM Digital Library version of record — de-anonymizing the sigconf source
- SKILL.md covers What changes between the…, The ACM production sequence, Digital Library metadata that… and Artifacts at publication time, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Sigir Camera Ready is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when an accepted SIGIR paper must become the ACM Digital Library version of record — de-anonymizing the sigconf source, CCS concepts and keywords, the e-rights form, TAPS source upload and proof checking, restoring real system and dataset names, and the April camera-ready window before the July conference.
Its SKILL.md is about 1.7k 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
- An accepted SIGIR paper must become the ACM Digital Library version of record — de-anonymizing the sigconf source
- CCS concepts and keywords
- The e-rights form
- TAPS source upload and proof checking
Example prompts
- “/sigir-camera-ready”
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- e-rights: the contact author receives ACM's rights form; completing it stamps
- TAPS upload: zip your LaTeX (or Word) source per the instructions in the
- Proofs: check both renderings. Tables that were hand-tuned for two-column PDF
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 (its code samples are bash).
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
Sigir Camera Ready loads about 1.7k tokens when it runs. Until then it costs about 83 tokens; SKILL.md has 815 words of instructions outside code blocks.
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). 815 words, ~1,723 tokens.
Download SKILL.mdSave it as
.claude/skills/sigir-camera-ready/SKILL.md (or your agent's skills folder).- name
- sigir-camera-ready
- description
- Use when an accepted SIGIR paper must become the ACM Digital Library version of record — de-anonymizing the sigconf source, CCS concepts and keywords, the e-rights form, TAPS source upload and proof checking, restoring real system and dataset names, and the April camera-ready window before the July conference.
SIGIR Camera Ready
SIGIR publishes through ACM: the version of record is produced by ACM's pipeline (e-rights, then TAPS) from your source files, and it appears in the Digital Library as both PDF and HTML (SIGIR 2025's volume is DOI 10.1145/3726302). The 2026 camera-ready window sat in late April for the tracks whose dates were verifiable (April 29, 2026 for Resources / Low Resource Environments); take your own track's date from the acceptance email, and note the July conference leaves little slack.
What changes between the reviewed PDF and the record
| Item | Reviewed submission | Version of record |
|---|---|---|
| Document class | sigconf + anonymous/review options | sigconf with rights commands from TAPS |
| Authors | Hidden | Restored; order frozen before e-rights |
| System name | Possibly a review alias | Real name, consistent with the public repo |
| Dataset/log provenance | Genericized for anonymity | As precise as data agreements allow |
| Repository link | Anonymous mirror | Public, licensed, stable (archival DOI best) |
| Acknowledgments | Absent | Restored — and they cost body pages at SIGIR |
| CCS concepts + keywords | Often placeholders | Final; they drive DL search forever |
| Leaderboard references | Scrubbed | Restorable — align run IDs with the paper |
Two SIGIR-specific pressure points hide in that table:
- Acknowledgments and restored details consume the page budget, because SIGIR counts everything except references inside the limit. If the camera-ready allowance for your track is the same as submission (whether acceptance buys an extra page was not verifiable for 2026 — 待核实), something you wrote must shrink to make room.
- The anonymity aliases must be unwound consistently. A paper that called its system "ANON-RANK" in review must not leave one stale alias in a figure caption or a run-file name cited in a table. Grep, don't skim.
The ACM production sequence
- e-rights: the contact author receives ACM's rights form; completing it stamps the copyright block, so title and author list must be final first.
- TAPS upload: zip your LaTeX (or Word) source per the instructions in the
acceptance email. TAPS compiles the DL's PDF and HTML5 — HTML is where homemade
macros,
\vspacehacks, and missing figure files fail loudly. - Proofs: check both renderings. Tables that were hand-tuned for two-column PDF are the usual HTML casualties, and IR papers are table-heavy.
# Sweep before zipping for TAPS
grep -rn "ANON\|anonym" *.tex sections/ # stale review aliases
grep -rn "4open\|anonymous.4open" *.tex # anonymous mirror still linked?
grep -rn "vspace\|renewcommand{\\\\baselinestretch}" *.tex # spacing hacks
ls figures/ | wc -l && grep -c includegraphics *.tex # figure inventory matchDigital Library metadata that outlives the conference
- CCS concepts: pick from the ACM taxonomy deliberately (e.g., Information systems → Retrieval models and ranking / Evaluation of retrieval results). They are the DL's routing layer for your paper's entire life.
- Keywords: include the terms IR searchers actually use — task name, collection names, method family ("dense retrieval," "learning to rank," "conversational search"). Your future citers search the DL and Google Scholar with these.
- Author name forms: match each author's existing DL record; inconsistent forms split citation identities.
- ORCID and funding: attach ORCIDs; format grants the way the funder mandates.
- The abstract in TAPS metadata must equal the PDF abstract — the DL indexes metadata.
Show full SKILL.md (347 more words)Show less
Artifacts at publication time
The camera-ready is the moment review-time artifacts become public commitments:
- Flip the repository public before the camera-ready deadline and test it from a logged-out browser; the paper will cite it for decades.
- Freeze the exact run files behind every table (
runs/with a manifest); IR replication requests are usually "can you send the run file," and yes should be easy. - If the paper introduced judgments, topics, or a corpus and it was not routed through the Resources track, publish it with a license and a datasheet anyway — the community treats missing licenses as unusable resources.
Worked example: absorbing review debts into the budget
An accepted full paper carries two commitments from the review phase: a promised scope-limitation paragraph and a clarification of the tuning protocol. Camera-ready also restores acknowledgments (~0.15 pp) and real provenance details (~0.1 pp). With no verified extra page, the arithmetic forces trades:
- Review commitments land first — they are quasi-contractual and reviewers of record may check.
- The restored acknowledgments displace the weakest analysis sentence-by-sentence, not table-by-table: prose compresses, protocol does not.
- Nothing new enters: results and claims not seen by reviewers do not belong in the version of record; they belong in the repository changelog or the next paper.
The heuristic: camera-ready pays debts and restores identity; it does not buy new real estate.
Registration and presentation
Author registration by the camera-ready date was confirmed for the Resources track in 2026 (April 29); whether every accepted full/short paper requires a registered, in-person presenting author — and the fee schedule — was not verifiable at build time (待核实). Read the acceptance email as the controlling document, and budget for Melbourne travel early: July is conference high season in the IR calendar.
Timeline discipline
- Week 0 (decision): settle author order; start e-rights; unwind aliases in source.
- Week 1: TAPS dry run with rights commands stubbed; fix class-file violations.
- Week 2: metadata pass (CCS, keywords, ORCID); repository public; proofs checked.
- Slack: TAPS support queues lengthen as thousands of ACM camera-readies converge — finishing a week early is the only reliable mitigation.
Output format
[Camera-ready status] on-track / blocked-at-rights / blocked-at-TAPS / not started
[Page budget] <pages>/<track allowance> (allowance verified from acceptance email? y/n)
[De-anonymization] aliases unwound y/n, repo public y/n, provenance restored y/n
[Metadata] CCS final / keywords final / ORCIDs attached / abstract == PDF
[Artifacts] run files frozen / license present / archival DOI minted
[Registration] requirement confirmed from acceptance email? y/n (fees 待核实)© 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 SIGIR-Skills/skills/sigir-camera-ready of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Sigir Camera Ready 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Sigir Camera Ready this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.7k | Automated safety check: Pass | MIT | |
| Digital Forensicssickn33/agentic-awesome-skills | 47k | 1 repos | ~495 | Automated safety check: Pass | MIT | |
| Digital Forensicszhaoxuya520/reverse-skill | 41k | 2 repos | ~389 | Automated safety check: Warn | MIT | |
| QA Acceptancepaperclipai/paperclip | 99k | — | ~964 | Automated safety check: Pass | MIT | |
| Acceptance Orchestratorsickn33/agentic-awesome-skills | 47k | 2 repos | ~943 | Automated safety check: Pass | MIT | |
| Acceptance Evidence for Deliverieslobehub/lobehub | 83k | — | ~9.7k | Automated safety check: Pass | Apache-2.0 |
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Acceptance Orchestrator
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Acceptance Evidence for Deliveries
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Questions about Sigir Camera Ready
What does Sigir Camera Ready do?
A skill your agent uses when an accepted SIGIR paper must become the ACM Digital Library version of record — de-anonymizing the sigconf source, CCS concepts and keywords, the e-rights form, TAPS…. Sigir Camera Ready is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when an accepted SIGIR paper must become the ACM Digital Library version of record — de-anonymizing the sigconf source, CCS concepts and keywords, the e-rights form, TAPS source upload and proof checking, restoring real system and dataset names, and the April camera-ready window before the July conference.
When should I use Sigir Camera Ready?
Sigir Camera Ready fits situations like: an accepted SIGIR paper must become the ACM Digital Library version of record — de-anonymizing the sigconf source; CCS concepts and keywords; the e-rights form; TAPS source upload and proof checking.
How do I install Sigir Camera Ready in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigir-camera-ready -a claude-code`. Or copy the skill folder (SIGIR-Skills/skills/sigir-camera-ready in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/sigir-camera-ready in your project. Claude Code loads it when a task matches its description.
How do I install Sigir Camera Ready in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigir-camera-ready -a codex`. Or copy the skill folder (SIGIR-Skills/skills/sigir-camera-ready in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/sigir-camera-ready in your project. Codex loads it when a task matches its description.
Can I use Sigir Camera Ready 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 sigir-camera-ready -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sigir-camera-ready, .gemini/skills/sigir-camera-ready, .github/skills/sigir-camera-ready and .opencode/skills/sigir-camera-ready in your project.
What does Sigir Camera Ready need to run?
SKILL.md names no scripts, command-line tools or credentials: Sigir Camera Ready is instructions for the agent only.
Does Sigir Camera Ready 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 Sigir Camera Ready 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 Sigir Camera Ready use?
Sigir Camera Ready 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 Sigir Camera Ready use?
About 1.7k tokens (SKILL.md is roughly 6.9k 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 Sigir Camera Ready?
Skills that share tags, products or a category with Sigir Camera Ready: Digital Forensics (sickn33/agentic-awesome-skills, 47k stars), Digital Forensics (zhaoxuya520/reverse-skill, 41k stars), QA Acceptance (paperclipai/paperclip, 99k stars) and Acceptance Orchestrator (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sigir Camera Ready?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,231 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.