01 Paper Review
agentscope-ai/OpenJudge
Review academic papers for correctness, quality, and novelty using OpenJudge's multi-stage pipeline.
Build auditable peer-review revision and author-response packages for Light stage 13.
$ npx skills add Light0305/Light-skills --skill light-review-rebuttal -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Light0305/Light-skills light-review-rebuttal --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/Light0305/Light-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/light-review-rebuttal .claude/skills/light-review-rebuttal && 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 "light-review-rebuttal" agent skill from https://github.com/Light0305/Light-skills/tree/master/skills/light-review-rebuttal into .claude/skills/light-review-rebuttal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "light-review-rebuttal", 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/Light0305/Light-skills/tree/master/skills/light-review-rebuttalType 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 Light0305/Light-skills --skill light-review-rebuttal -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Light0305/Light-skills light-review-rebuttal --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Light0305/Light-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/light-review-rebuttal .agents/skills/light-review-rebuttal && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "light-review-rebuttal" agent skill from https://github.com/Light0305/Light-skills/tree/master/skills/light-review-rebuttal into .agents/skills/light-review-rebuttal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "light-review-rebuttal", 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 Light0305/Light-skills --skill light-review-rebuttal -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Light0305/Light-skills light-review-rebuttal --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Light0305/Light-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/light-review-rebuttal .cursor/skills/light-review-rebuttal && 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 "light-review-rebuttal" agent skill from https://github.com/Light0305/Light-skills/tree/master/skills/light-review-rebuttal into .cursor/skills/light-review-rebuttal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "light-review-rebuttal", 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/Light0305/Light-skills.git --path skills/light-review-rebuttal--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 Light0305/Light-skills --skill light-review-rebuttal -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Light0305/Light-skills light-review-rebuttal --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Light0305/Light-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/light-review-rebuttal .gemini/skills/light-review-rebuttal && 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 "light-review-rebuttal" agent skill from https://github.com/Light0305/Light-skills/tree/master/skills/light-review-rebuttal into .gemini/skills/light-review-rebuttal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "light-review-rebuttal", 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 Light0305/Light-skills light-review-rebuttalInstalls 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 Light0305/Light-skills --skill light-review-rebuttal -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Light0305/Light-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/light-review-rebuttal .github/skills/light-review-rebuttal && 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 "light-review-rebuttal" agent skill from https://github.com/Light0305/Light-skills/tree/master/skills/light-review-rebuttal into .github/skills/light-review-rebuttal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "light-review-rebuttal", 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 Light0305/Light-skills --skill light-review-rebuttal -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Light0305/Light-skills light-review-rebuttal --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Light0305/Light-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/light-review-rebuttal .opencode/skills/light-review-rebuttal && 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 "light-review-rebuttal" agent skill from https://github.com/Light0305/Light-skills/tree/master/skills/light-review-rebuttal into .opencode/skills/light-review-rebuttal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "light-review-rebuttal", 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.
light-review-rebuttalBuild auditable peer-review revision and author-response packages for Light stage 13.
Light Review Rebuttal is an agent skill from Light0305/Light-skills. Build auditable peer-review revision and author-response packages for Light stage 13. Use after receiving reviewer comments, a decision or meta-review; when drafting a rebuttal or response letter; when triaging major/minor revisions; when simulating a pre-submission review; or when a rejection may require a user-chosen 13→3 novelty, 13→5 experiment, or 13→8 writing back-edge. Consumes the selected venue/context and real PDF facts, preserves reviewer wording, atomizes issues, binds…
Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 22 other files, including scripts and reference files (for example `agents/openai.yaml`, `references.md` and `references/workflow_contract.md`).
It sits in Research & Science, covering Peer review, Citation management and PDF. The repository describes itself as: An AI workflow skill pack for research, competitions, and innovation projects. The licence is MIT.
7 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 6b44f57. It shows what the files ask for, not the result of running them.
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.
Ships 7 files in scripts/ (Python, from the files we listed), which the agent can run.
Shell commands in SKILL.md call:
pythonFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Light Review Rebuttal loads about 3.5k tokens when it runs, and up to ~4.9k if it reads all its reference files. Until then it costs about 192 tokens; SKILL.md has 1,391 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.
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); the scripts in this folder are not scanned.
The full file from Light0305/Light-skills at commit 6b44f57, republished under its MIT licence (© Light0305). 1,391 words, ~3,529 tokens.
.claude/skills/light-review-rebuttal/SKILL.md (or your agent's skills folder). This skill also uses 18 other files; get the full folder from GitHub.Build a source-preserving review registry, issue matrix, revision plan, evidence/change map, response draft, commitment ledger, unknown/failure record, and delivery package. Treat prose generation as the last layer, not the first.
Read review-rebuttal-resource-map.md before
a real run. Read
references/workflow_contract.md before
creating or consuming canonical JSON. Read references.md
when selecting review/rule sources. The competitor evidence is
../../docs/competitors/review-rebuttal.md.
selected_at timezone, selection_basis, user/delegated
authorization, chosen candidate ID, fit/risk row, unmodified rule envelopes,
source evidence path/as-of/source IDs, manuscript profile, and PDF
path/hash/pages/page size/profile/compliance. Never switch venue, reorder
tiers, or turn venue UNKNOWN into a fact.AVAILABLE|UNKNOWN|UNAVAILABLE|STALE. A 401/403/429/5xx, timeout, login,
private invitation or network failure is UNAVAILABLE, not “no review.”PLANNED and IN_PROGRESS may not
be phrased as completed. DONE requires a real change locator; completed
experiment/analysis additionally requires verifiable run provenance with a
matching SHA-256, not merely a local path.
Before marking a response package ready, run the atom/action contract gate so
source spans, reconstruction hashes, policy/ethics authorization and
perspective-specific self-review are machine-checked rather than trusted.novelty|experiment|writing) explicitly marked rejection_driving=true
with a complete decision/meta-review/reviewer evidence envelope may become
critical. Major labels or an overall Reject alone do not make every comment
critical.reviewer_classify and reroute produce advice only. Stop after presenting
evidence and alternatives. Run passport add-back-edge only after the user
chooses the root cause/back-edge. Never mutate the passport automatically.Require:
light.selected_venue_handoff.v1;light.review_rebuttal_venue_context.v1;light.paper_claims.v1;light.evidence_strength.v1;Run:
python scripts/review_workflow.py \
--spec review-input.json \
--outdir review-deliveryIf venue identity, rule envelopes, PDF hash, compliance, claims or evidence IDs do not agree, stop and repair the producer artifact. Do not “normalize” a conflict away.
The selected handoff must also retain A32's audit fields: timezone-bearing
selected_at that is not in the future, non-empty selection_basis,
decision_authority=user, coherent selected_by/status, delegated
user_authorization when applicable,
unchanged fit_risk, and a readable source_evidence.path whose SHA-256
matches the selected handoff and whose as_of/source_ids cover every sourced
venue rule.
For user-provided/private material, copy the text into reviews[].raw_text
without correction and record reviews[].raw_sha256 plus a timezone-aware
captured_at; the workflow re-computes the hash and blocks future/naive capture
times. For a public OpenReview forum:
python scripts/fetch_openreview.py \
--forum <forum-id> \
--out openreview-capture.jsonIf the live API is unavailable but a fixed public PeerRead/OpenReview snapshot is the declared evidence source, capture that exact commit-pinned JSON instead:
python scripts/fetch_openreview.py \
--peerread-url <raw-fixed-commit-json-url> \
--out peerread-capture.jsonThe capture is calibration/source evidence. Do not redistribute restricted reviews. If capture is unavailable, continue only with material the user provided and retain the failure record.
Create one atom for each distinct request, claim, question,
misunderstanding, or editorial item. Each atom must contain an exact
contiguous source span copied from raw_text, with start/end offsets, span
text and SHA-256. Also create addressable coverage units and a reconstruction
hash for the reviewer units that require a response.
Assign one root cause such as novelty, experiment, writing,
clarification, citation, ethics, scope, or editorial. Add a separate
interpretation explaining the inferred concern. If a sentence contains two
independent asks, create two atoms pointing to the same or overlapping source
span; do not paraphrase the reviewer into a new source quote.
Run the stricter losslessness/response-action gate before drafting:
python scripts/review_response_contract.py \
--input templates/review-response-contract.example.jsonReplace the template with the real contract. The example is intentionally
non-passing until current venue policy, ethics state and user authorization are
verified. This gate catches missing reviewer units, duplicate atom/action
coverage, fake DONE wording, incomplete evidence kinds, policy-forbidden
reviewer requests, missing reviewer competence/conflict cards, and missing
domain|method|statistics|ethics|cold_reader self-review perspectives.
For every atom:
claim_id values or leave the list empty;acknowledge_and_fix, rebut_with_evidence, clarify,
downgrade_claim, or request_editor_ruling;PLANNED|IN_PROGRESS|DONE|DECLINED|NOT_APPLICABLE;DONE experiment/analysis the artifact path must exist and match
run_provenance.sha256;CONFIRMED.Reviewer error is not permission to ignore a comment. Clarify with manuscript locator and evidence, or request editor ruling when the disagreement is material.
When a reviewer request itself conflicts with venue policy, ethics approval,
data rights, consent, budget authorization or editor instructions, do not
silently comply. Mark the action as DECLINED or REQUEST_RULING, bind the
policy/ethics evidence, and keep the reviewer wording intact.
Run:
python scripts/rebuttal_budget.py \
review-delivery/response-draft.md \
--context review-rebuttal-context.jsonAn AVAILABLE current authoritative rule can yield PASS/FAIL. UNKNOWN,
UNAVAILABLE, STALE, or a page-only rule stays non-passing and explicit.
Never apply an ICLR/CVPR/other venue preset to JORS or vice versa.
For every reviewer request for new numbers/experiments, classify it before any run as reanalysis/minimal/adapted/new-data plus feasibility and intended action:
python scripts/experiment_request_gate.py \
--input templates/experiment_request.example.jsonThe template is intentionally UNKNOWN and non-passing until current official
rules and a real user authorization replace its placeholders.
RUN requires a VERIFIED current venue rule with source_type=OFFICIAL, a real
source and ISO check date that allows new results, plus feasible scope, protocol,
budget and user authorization. Tier-D new data/human study/
large sweep needs separate authorization. This gate only permits a run;
DONE still requires run manifest + result artifact hash, and only then may
the response use completed tense.
Run:
python scripts/check_commitments.py \
--ledger review-delivery/commitment-ledger.json \
--issues review-delivery/issue-matrix.json \
--change-map review-delivery/evidence-change-map.jsonRepair every critical finding. A valid locator proves only that a claimed change is traceable, not that the scientific response is adequate; perform a human re-review against the actual revised artifact.
Run:
python scripts/reviewer_classify.py \
--issues review-delivery/issue-matrix.json \
--out reviewer-findings.json
python ../light-orchestrator/scripts/run_checkpoint.py \
--file .light/passport.yaml --stage 13 \
--findings reviewer-findings.json --ts <ISO-8601> --write
python ../light-orchestrator/scripts/reroute.py \
--findings reviewer-findings.json --stage 13 \
--passport .light/passport.yamlIf the gate fails, present each evidenced option:
Stop for the user's choice. Only then run:
python ../light-orchestrator/scripts/passport.py add-back-edge \
--to <3|5|8> --from 13 --root-cause "<user-approved reason>" \
--evidence-ptr <issue/evidence locator> --file .light/passport.yaml| Resource | Responsibility |
|---|---|
review-rebuttal-resource-map.md | execution order, source/access layers, cross-skill routing |
references/workflow_contract.md | schemas, statuses, invariants and artifact semantics |
references.md | live source policy, OpenReview/JORS caveats, verification guidance |
templates/* | blank author inputs and human-readable response/re-review shapes |
scripts/review_workflow.py | canonical validation and package emission |
scripts/review_response_contract.py | source-span/reconstruction, atom coverage, response-action evidence, policy/ethics, reviewer-card and self-review gate |
scripts/fetch_openreview.py | live API or fixed public snapshot capture; honest unavailable state and duplicate accounting |
scripts/reviewer_classify.py | only evidenced rejection-driving stage-13 findings |
scripts/check_commitments.py | coverage and PLANNED/DONE/provenance gate |
scripts/rebuttal_budget.py | selected-context budget assessment; no venue presets |
scripts/experiment_request_gate.py | venue-policy/feasibility/tier/authorization gate; never runs experiments |
captured_at and
raw_sha256; the registry hash matches the exact raw_text.DONE rows have real
locators; completed scientific actions have run provenance path + SHA-256
match; proposed citations are citation-confirmed.UNKNOWN.Atomization, triage, point-by-point drafting, tone guidance, reviewer priority, budgeting, change locators, promise tracking and venue adaptation are common in peer skills; do not claim them as unique. Light's narrower machine contribution is verified consumption of upstream venue/PDF/claim/evidence/citation contracts, immutable source versus interpretation layers, strict PLANNED/DONE/run-provenance checks, and evidence-gated stage-13 routing that cannot execute without a user decision. Classification and response quality still require expert judgment.
© Light0305, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 18 other files (scripts, references) in skills/light-review-rebuttal of Light0305/Light-skills.
Open the folder on GitHubat commit 6b44f57
Light Review Rebuttal 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 |
|---|---|---|---|---|---|---|
| Light Review Rebuttal this skillLight0305/Light-skills | 640 | — | ~3.5k | Automated safety check: Pass | MIT | |
| 01 Paper Reviewagentscope-ai/OpenJudge | 871 | — | ~2.4k | Automated safety check: Pass | Apache-2.0 | |
| Academic Paper Writing PipelineImbad0202/academic-research-skills | 51k | — | ~16k | Automated safety check: Pass | Custom licence | |
| Ref Downloaderltczding-gif/ref-downloader | 139 | — | ~5.9k | Automated safety check: Pass | MIT | |
| Obsidian Paper VaultAperivue/medsci-skills | 333 | — | ~1.6k | Automated safety check: Pass | MIT | |
| Research Vault Literature Retrievalcheneternity/Research-Vault-Literature-Retrieval | 292 | — | ~2.3k | Automated safety check: Pass | None |
agentscope-ai/OpenJudge
Review academic papers for correctness, quality, and novelty using OpenJudge's multi-stage pipeline.
Imbad0202/academic-research-skills
Runs a 12-agent pipeline that plans, drafts, cites, reviews and formats academic papers, with modes for revision, rebuttals, abstracts and citation checks.
ltczding-gif/ref-downloader
A skill your agent uses when the user asks to batch-download academic PDFs with ref-downloader — either ALL references of one paper (Mode A: DOI or PDF input), OR a custom batch of papers (Mode B…
Aperivue/medsci-skills
A skill your agent uses when turning a folder of research PDFs into Obsidian notes, even if Obsidian is not named.
cheneternity/Research-Vault-Literature-Retrieval
ResearchVault 文献知识问题的默认检索技能。先从当前 Vault 的 Analytical Notes 定位相关论文,再按需要定向进入对应 Fulltext,必要时回到 Zotero PDF 验证。若用户明确要求基于当前项目文件检索,优先执行严格的项目文件检索后再回答。纯 Skill、代码、Git、文件整理和转换工具调试任务不自动触发文献检索。
MrGeDiao/paper-reading-zh
中文论文深读、总结/TL;DR、工程拆解、按论文实现/复现、比较与证据审计。用户给出论文 PDF、链接、标题、摘要、正文或图表,或明确要读论文时使用。只有论文锚点且无附言时澄清阅读目标;只有阅读意图时问哪篇。已有论文时,“看看这篇”直接深读。不用于仅翻译、解释单个术语、生成 BibTeX、找或下载论文。
Light0305/Light-skills
Verifies that every reference in a manuscript is real, correctly identified and actually supports its claim, and produces a citation registry for typesetting.
Light0305/Light-skills
Coordinates and recovers multi-stage Light research projects from a single passport file, with checkpoints, stale-work tracking and rerouting only when you approve.
Light0305/Light-skills
Builds an evidence-backed invention disclosure packet from a project or research result for attorney or patent-agent review, without giving legal advice.
Light0305/Light-skills
Audits, scaffolds and safely migrates research project folder structures, keeping existing repositories read-only until you approve exact moves from a plan.
Light0305/Light-skills
Prepares draft materials for a China software copyright registration from a real project: application worksheet, source deposit plan, operation manual and consistency checks.
Light0305/Light-skills
Evidence-based workflow for designing or modernizing a software system: current-state inventory, options, API and schema contracts, migration plans, ADRs and verification.
Categories
Build auditable peer-review revision and author-response packages for Light stage 13. Light Review Rebuttal is an agent skill from Light0305/Light-skills. Build auditable peer-review revision and author-response packages for Light stage 13.
Light Review Rebuttal fits situations like: tasks that involve Peer review; tasks that involve Citation management; tasks that involve PDF.
Run `npx skills add Light0305/Light-skills --skill light-review-rebuttal -a claude-code`. Or copy the skill folder (skills/light-review-rebuttal in Light0305/Light-skills) into .claude/skills/light-review-rebuttal in your project. Claude Code loads it when a task matches its description.
Run `npx skills add Light0305/Light-skills --skill light-review-rebuttal -a codex`. Or copy the skill folder (skills/light-review-rebuttal in Light0305/Light-skills) into .agents/skills/light-review-rebuttal in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Light0305/Light-skills --skill light-review-rebuttal -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/light-review-rebuttal, .gemini/skills/light-review-rebuttal, .github/skills/light-review-rebuttal and .opencode/skills/light-review-rebuttal in your project.
Going by SKILL.md and its folder, Light Review Rebuttal needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
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.
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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Light Review Rebuttal is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.4k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Light Review Rebuttal: 01 Paper Review (agentscope-ai/OpenJudge, 871 stars), Academic Paper Writing Pipeline (Imbad0202/academic-research-skills, 51k stars), Ref Downloader (ltczding-gif/ref-downloader, 139 stars) and Obsidian Paper Vault (Aperivue/medsci-skills, 333 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Light0305 (a GitHub user) maintains it in Light0305/Light-skills, which has 640 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on July 6, 2026.
Source: Light0305/Light-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.