Agent skill

Review Cluster

by flonat in flonat/flonat-research

Deliver a mid-draft adversarial review of a paper — runs paper-critic + domain-reviewer + claim-verify + blindspot in parallel, optionally adds clarity-reviewer, then auto-synthesises into a…

MITAuto-check passed

Install Review Cluster

skills CLI
$ npx skills add flonat/flonat-research --skill review-cluster -a claude-code

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

GitHub CLI
$ gh skill install flonat/flonat-research review-cluster --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/flonat/flonat-research.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/review-cluster .claude/skills/review-cluster && 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
review-cluster
GitHub stars
146
Token cost
~4.9k tokens
SKILL.md length
1,979 words
Files
1
Skills in repo
83
Repo updated
First seen
Licence
MIT

At a glance

Deliver a mid-draft adversarial review of a paper — runs paper-critic + domain-reviewer + claim-verify + blindspot in parallel, optionally adds clarity-reviewer, then auto-synthesises into a…

  • Works in 5 steps: Pre-flight → Dispatch → Math verification (theory papers only) → …
  • The user requests a mid-draft adversarial review of a paper — runs paper-critic + domain-reviewer + claim-verify + blindspot in parallel
  • SKILL.md covers Output Path, Hard Rules, When to Use and When NOT to Use, plus 11 more sections
  • Calls bash

What it does

Review Cluster is an agent skill from flonat/flonat-research. Deliver a mid-draft adversarial review of a paper — runs paper-critic + domain-reviewer + claim-verify + blindspot in parallel, optionally adds clarity-reviewer, then auto-synthesises into a prioritised revision plan. Use when the user requests a mid-draft adversarial review of a paper — runs paper-critic + domain-reviewer + claim-verify + blindspot in parallel, optionally adds clarity-reviewer, then auto-synthesises into a prioritised revision plan. Distinct from pre-submission-report (final-gate kitchen sink…

Its SKILL.md is about 4.9k 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: Shareable Claude Code + Codex infrastructure for PhD researchers — skills, agents, hooks, and rules for academic workflows. The licence is MIT.

When your agent uses it

  • The user requests a mid-draft adversarial review of a paper — runs paper-critic + domain-reviewer + claim-verify + blindspot in parallel
  • Optionally adds clarity-reviewer
  • Then auto-synthesises into a prioritised revision plan

Example prompts

  • “review my draft”
  • “adversarial review”
  • “cluster review”
  • “/review-cluster”

Requirements

  • Pre-approved tools (allowed-tools): Read, Glob, Grep, Bash(uv*), Bash(ls*), Bash(git*), Task, Skill, AskUserQuestion

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Pre-flight
  2. Dispatch
  3. Math verification (theory papers only)
  4. Consolidate
  5. Report

What it can do on your machine

Read from SKILL.md and the folder at commit da27600. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Glob
    • Grep
    • Bash(uv*)
    • Bash(ls*)
    • Bash(git*)
    • Task
    • Skill
    • AskUserQuestion

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • 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

Review Cluster loads about 4.9k tokens when it runs. Until then it costs about 178 tokens; SKILL.md has 1,979 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~178
When it runs · the whole SKILL.md, loaded when a task matches
~4.9k

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 flonat/flonat-research at commit da27600, republished under its MIT licence (© flonat). 1,979 words, ~4,914 tokens.

Download SKILL.mdSave it as .claude/skills/review-cluster/SKILL.md (or your agent's skills folder).
name
review-cluster
description
Deliver a mid-draft adversarial review of a paper — runs paper-critic + domain-reviewer + claim-verify + blindspot in parallel, optionally adds clarity-reviewer, then auto-synthesises into a prioritised revision plan. Use when the user requests a mid-draft adversarial review of a paper — runs paper-critic + domain-reviewer + claim-verify + blindspot in parallel, optionally adds clarity-reviewer, then auto-synthesises into a prioritised revision plan. Distinct from pre-submission-report (final-gate kitchen sink, 14 checks) — this is the active-drafting feedback loop. Triggers: 'review my draft', 'adversarial review', 'cluster review', 'mid-draft critique', 'feedback before pre-submission'.
allowed-tools
Read, Glob, Grep, Bash(uv*), Bash(ls*), Bash(git*), Task, Skill, AskUserQuestion
argument-hint
[paper-path or no-args (auto-detect)] [--clarity] [--no-synthesise]
agent-dependencies
paper-critic, domain-reviewer, claim-verify, blindspot, clarity-reviewer
skill-dependencies
latex, pre-submission-report, review-packet, strategic-revision, synthesise-reviews, verify-math

Review Cluster — Mid-Draft Adversarial Feedback

Parallel fan-out of a 4-agent read-only core on an active-drafting paper, optionally adding clarity-reviewer as a fifth agent, with auto-synthesise downstream. Lighter than pre-submission-report --parallel; designed for tight iteration, not final-gate verification. Outputs reviews/<scope>/review-cluster/YYYY-MM-DD-cluster-report.md (scope = paper slug from the paper path).

Output Path

Per rules/review-artefact-routing.md (auto-loads in research projects (path-scoped to paper-*/ and paper/)):

  • Source slug: review-cluster
  • Write reports to: reviews/<scope>/review-cluster/YYYY-MM-DD.md (scope = paper slug) inside the project. Path is relative to the research project root, not the Task-Management repo.
  • Never at project root (./CRITIC-REPORT.md-style filenames are forbidden — pre-rule layout).
  • Idempotency: if today's file exists, append a same-day descriptor ({date}-revision.md, {date}-r2.md, {date}-pre-submission.md) — never overwrite.
  • Index policy: the consolidated cluster report is an output-only artefact and receives no Check=review-cluster row. Each active reviewer receives its own row with Trigger=review-cluster.
  • Infrastructure repos (Task-Management, atlas-workspace, etc.): this section does not apply — the path-scoped rule won't load there.

Hard Rules

Existential — block output
  1. All active sub-agents are read-only. No git, no latexmk, no edits. See subagent-write-guard.md.
  2. Auto-synthesise via synthesise-reviews (unless --no-synthesise). Mid-draft work needs an actionable revision plan, not 4 raw reports.
  3. Skip if paper isn't compile-ready — run latex first; review on broken builds is misleading. The skill checks compile-status before dispatching.
  4. Cluster is for the user's own papers. For external papers, use peer-reviewer agent instead.
  5. Prepare one common review input. After compile preflight, invoke review-packet in fresh-review mode unless the user explicitly supplies a verified packet or requests --no-freeze-input. Record the packet archive hash and canonical PDF hash in every reviewer prompt and in the consolidated report. Packet creation itself creates no reviews/INDEX.md verdict row.
Format — catch in review
  1. Write one consolidated cluster report at reviews/<scope>/review-cluster/YYYY-MM-DD-cluster-report.md (scope = paper slug), in addition to the required per-agent reports and INDEX rows.
  2. Findings tiered M/m/n (Major / moderate / minor) per severity-gradient.md.
  3. Show which sub-agent flagged each finding (audit trail for traceability).
  4. Clarity on request. With --clarity (or when the paper's prior referee reviews contain readability complaints), add clarity-reviewer as a 5th parallel agent — reader-experience stall map + the 10 clarity diagnostic classes. Its findings join the synthesis like the others.
  5. Yardstick continuity on repeat runs. When a prior cluster report exists for the same paper (reviews/<scope>/review-cluster/), the new run reuses the prior run's frozen yardstick — same phase banner (severity-gradient), same rubric set, and the prior findings list passed to the agents as "verify addressedness + new issues only", never a fresh re-derivation of criteria from the revised text (scores across rounds must be comparable; a moved yardstick fakes improvement). If the prior report is unavailable or the user explicitly resets the phase, mark the report [YARDSTICK-REGENERATED: <reason>] under the phase banner. (Ported from ARS v3.19 re-review protocol, 2026-07-24.)

When to Use

  • Active drafting: paper compiles, content is taking shape, want adversarial feedback before final polish
  • Mid-revision: addressed first round of supervisor comments; want fresh perspective before next pass
  • Pre-pre-submission: ~2 weeks before submission, want to surface major issues with time to address
  • Before sharing draft with co-authors

When NOT to Use

  • Paper is in final pre-submission state — use pre-submission-report --parallel (13 sub-agents, full kitchen sink)
  • Paper is in early scaffold (introduction only, no method/results) — review will flag everything as missing
  • Reviewing someone else's paper — use peer-reviewer agent
  • R&R revision response — use strategic-revision --external instead (genuine venue-comment-driven)

Modes

InvocationBehaviour
review-clusterFull 4-agent fan-out + auto-synthesise
review-cluster <paper-path>Same, explicit paper
review-cluster --no-synthesiseRun agents in parallel; show 4 raw reports without merging
review-cluster --clarityAdd clarity-reviewer as the 5th agent; include its report in stamping and synthesis
review-cluster --no-freeze-inputReview the live compile-ready source without sealing a packet; record this weaker snapshot regime explicitly

Architecture

Phase 1 (preflight) → latex compile check + decision-ready manuscript review packet; abort if broken
Phase 2 (dispatch)  → 4 core read-only sub-agents, plus optional clarity-reviewer, in parallel
Phase 3 (math)      → IF theory paper: verify-math on the model section(s) [orchestrator-run skill]
Phase 4 (consolidate) → synthesise-reviews merges (incl. math verdict) → revision plan
Phase 5 (report)    → reviews/<scope>/review-cluster/YYYY-MM-DD-cluster-report.md

The 4-agent core and optional clarity reviewer

#AgentWhy this lens
1paper-critic (specialist mode if venue known)General adversarial — structural issues, argument quality, contribution clarity. Most-cited reviewer in the family.
2domain-reviewerMath derivations, assumption completeness, citation fidelity at the substantive level, code-theory alignment. Catches what paper-critic doesn't have the lens for.
3claim-verifyCitation fidelity at the per-claim level — does what's written about Smith (2024) actually match Smith (2024)? Distinct from bib-validate (existence) and paper-critic (structure).
4blindspotPeripheral-vision audit — vices in plain sight + virtues being overlooked. Distinct from adversarial review because it surfaces missed opportunities, not just things to fix.
5 (optional)clarity-reviewerReader-ingestion stress test. Added with --clarity or when prior referee reviews contain readability complaints.

Why these four form the default core:

  • referee2-reviewer is excluded — it's the final-stage hostile review, used in pre-submission-report. Mid-draft, hostile review pre-empts genuine improvement.
  • artifact-coherence-auditor / reproducibility-auditor are excluded — relevant only when the paper is paired with a replication artifact, which is typically a pre-submission concern.
  • code-paper-auditor is excluded — a separate code-suite skill exists for code-side review.
  • proofread is excluded — editorial issues are too noisy mid-draft; deferred to pre-submission.
Dispatch contract (evidence-grounded findings)

When dispatching the active reviewer set (Phase 2), each prompt MUST carry the evidence clause from _shared/audit-integrity.md: every finding cites path:line (or §section) AND quotes the exact text it is about, verbatim — no quotable anchor, no finding. Phase 4 (synthesise-reviews) spot-verifies a sample and drops anything it cannot ground, so an agent that emits unanchored findings simply loses them. Tell the agents this up front so they anchor everything.

Phase 1: Pre-flight

bash
# Auto-detect paper or use arg
PAPER_PATH="${1:-$(ls -d paper-*/paper 2>/dev/null | head -1)}"
[ -z "$PAPER_PATH" ] && echo "No paper-*/ directory found" && exit 1

# Check compile-readiness — exit if last latex run failed
LATEST_PDF=$(find "$PAPER_PATH/out" -name "*.pdf" -newer "$PAPER_PATH/main.tex" 2>/dev/null | head -1)
if [ -z "$LATEST_PDF" ]; then
    echo "Paper not compiled or stale. Run latex first."
    # the available structured-question mechanism: run latex now, or proceed anyway (risky)?
fi

Phase 2: Dispatch

Construct the active reviewer set as paper-critic, domain-reviewer, claim-verify, and blindspot; append clarity-reviewer when --clarity is set or prior referee reviews contain readability complaints. Launch every active reviewer in a single parallel dispatch. Each gets:

  • Read-only with respect to project files under review — Read, Glob, Grep, Bash (read-only commands only) against the paper / code being reviewed; the agent does NOT modify any project source files

  • The standard forbid-list from subagent-write-guard.md

  • Paper path explicitly named

  • Frozen review identity — the common review-packet path, archive SHA-256, and canonical PDF SHA-256. Reviewers may read the project for anchors, but findings must be compatible with that frozen artifact; if live source has drifted, stop and regenerate the packet.

  • Output target — two-step, both required:

    1. Write the per-agent report to reviews/<scope>/<source-slug>/<YYYY-MM-DD-HHMM>.md (scope = paper slug, source-slug = agent name like paper-critic; run mkdir -p reviews/<scope>/<source-slug>/ first), then emit the standard stamp directive. The orchestrator-side propagation step appends the durable INDEX row.
    2. Return a structured findings summary to the orchestrator for the Phase 4 consolidate step.

    These two outputs are NOT mutually exclusive. The file under reviews/<source-slug>/ is the durable artefact and triggers the row stamp; the structured return value is the orchestrator's working copy for consolidation. Earlier wording — "not a file write" — was wrong: it suppressed the per-agent logging step and resulted in 0–1 of 4 cluster dispatches stamping a row in INDEX.md. The 2026-05-17 5-agent patch (commit 23ebcfff) made the agent-side intro unconditional; this dispatch-side fix is the orchestrator-side complement.

Wait for every active reviewer. Do not start Phase 4 (consolidate) until all return.

Show full SKILL.md (900 more words)Show less

Phase 3: Math verification (theory papers only)

The 4-agent fan-out covers the conceptual math layer (via domain-reviewer, rung R0) but does not run the computational verification rungs. For a theory paper, add a verify-math pass so the algebra/analytic claims are machine-checked, not just read.

Detect a theory paper (any of):

bash
grep -lE '\\begin\{(theorem|proposition|lemma|corollary)\}' "$PAPER_PATH"/**/*.tex 2>/dev/null

If there are no formal environments, skip this phase entirely.

If it IS a theory paper, invoke verify-math (via the skill-routing mechanism) scoped to the section(s) holding the model — it decomposes each proposition into atomic obligations and routes them across the spectrum (R0 conceptual · R1 numerical falsification · R2 symbolic/CAS · R3 Lean). verify-math is a skill, run by this orchestrator in the main session — this is deliberate: the computational rungs (numerical-check, symbolic-check, lean-check) need Bash + sympy/lean, which sub-agents cannot reliably obtain at runtime (the same Bash-grant fragility documented below). The orchestrator always has Bash, so the rungs run here, not inside an agent.

verify-math writes its own aggregate report to reviews/<scope>/verify-math/<YYYY-MM-DD-HHMM>.md and stamps its own INDEX.md row (it is a self-stamping skill, like proofread). Fold its aggregate verdict — and any FALSIFIED obligation — into the Phase 4 synthesis as a high-confidence finding (a machine-falsified claim outranks any single reviewer's concern).

Avoid double-work: domain-reviewer (agent #2) and verify-math's R0 rung both cover the conceptual layer. When this phase runs, tell domain-reviewer in its dispatch prompt that the algebraic identities and comparative-static signs are being machine-verified separately, so it should focus on the conceptual obligations (assumption completeness, citation fidelity, backward logic) rather than re-deriving algebra — see the domain-reviewer "Math R0 Mode" preset.

Phase 4: Consolidate

If --no-synthesise: stop here and show every active reviewer's raw report.

Otherwise, invoke synthesise-reviews with every active reviewer's report as input. Output is a prioritised revision plan with:

  • Cross-reviewer agreement (claims raised by ≥2 reviewers — high confidence)
  • Single-reviewer claims (medium confidence)
  • Blindspot virtues (opportunities, not problems — sometimes the most valuable finding)
  • Recommended action queue with priority + estimated effort

Phase 5: Report

Save to reviews/<scope>/review-cluster/YYYY-MM-DD-cluster-report.md (scope = paper slug):

markdown
# Review Cluster Report — YYYY-MM-DD

**Paper:** <path>
**Compile status:** <PASS / WARN / FAIL>
**Review packet:** <path, archive SHA-256, canonical PDF SHA-256>
**Reviewers:** <active reviewer set; include clarity-reviewer when requested>

## Summary
- Major issues (M-tier): N
- Moderate (m-tier): N
- Minor (n-tier): N
- Blindspot virtues (opportunities): N

## Cross-reviewer agreement (high confidence)
| Issue | Severity | Flagged by |
|---|---|---|
| ... | M | paper-critic, domain-reviewer |

## Single-reviewer claims (medium confidence)
[Table by severity]

## Blindspot — virtues + missed opportunities
[Items from #4 sub-agent]

## Recommended action queue
1. [Highest-priority]
2. ...

Cross-References

Skill / Agent / RuleRelationship
pre-submission-report --parallelFinal-gate kitchen sink (14 checks) — this skill is the mid-draft analogue (4-agent core, optional 5th)
review-packetDefines and optionally seals the common manuscript decision surface reviewed by every agent
synthesise-reviewsThe merge step this skill invokes
strategic-revisionAfter this skill produces a synthesis, optionally hand it to strategic-revision --internal <synthesis-path> when interdependent issues need a DAG and critical path
paper-critic, domain-reviewer, claim-verify, blindspot, optional clarity-reviewer agentsThe active reviewer set this skill orchestrates
verify-mathPhase 3 node for theory papers — machine-verifies the math (R1/R2/R3 rungs the agents can't run); self-stamps its own report
code-suiteCode-side counterpart for projects with code
subagent-write-guard.mdSub-agents follow this rule (read-only forbid-list)
_shared/audit-integrity.mdRule 2 (finding-grounding): each reviewer must cite path:line + a verbatim quote; the orchestrator spot-verifies a sample before trusting findings
proofreadEditorial polish — run AFTER cluster review, before pre-submission-report

REVIEW-STATE.md propagation (orchestrator-side stamping)

This skill is an orchestrator in the REVIEW-STATE.md schema. As of the 2026-05-19 architecture change, the orchestrator (this skill) handles all stamping; sub-agents emit directives but do not call the helper themselves. Every active reviewer ends its final response with a review-state-stamp fenced block (see the installed shared resource _shared/stamp-directive-spec.md).

Required orchestrator behaviour

When constructing prompts for the active reviewer set, include this line in each:

Emit a review-state-stamp directive at the end of your final response per the installed shared resource _shared/stamp-directive-spec.md. Set trigger: review-cluster (or omit — this orchestrator overrides). Do not call the stamping helper yourself.

After all active reviewers return

For each sub-agent's return:

  1. Write the agent's final response to a temp file (/tmp/review-cluster-<agent>.md).
  2. Parse the directive:
    bash
    ARGS=$(bash <skills-root>/_shared/parse-stamp-directive.sh /tmp/review-cluster-<agent>.md)
    If parse-stamp-directive.sh exits non-zero, log a warning ("Agent X return did not contain a review-state-stamp directive") and continue with the next agent — best-effort.
  3. Verify the .md report file exists; reconstruct from return content if missing:
    bash
    VERIFY=$(bash <skills-root>/_shared/post-dispatch-verify.sh \
        --return-file /tmp/review-cluster-<agent>.md \
        --project "$PROJECT_ROOT" \
        --agent <agent>)
    # $VERIFY is 'OK <path>' or 'RECONSTRUCTED <path>'.
    # Exit code 10 means reconstruction happened — append a marker to the notes
    # so review-recap shows this row was a recovery, not a real run.
    If VERIFY starts with RECONSTRUCTED, append (report reconstructed by orchestrator — agent skipped Write) to the --notes value before stamping. This guards against the blindspot-class failure mode (agent claims to write but skips the call). See log/2026-05-21-blindspot-write-fix.md.
  4. Stamp with the orchestrator's --trigger override (overriding whatever the agent emitted):
    bash
    eval bash <skills-root>/_shared/review-state-log.sh "$ARGS" \
        --trigger review-cluster \
        --source agent \
        --project "$PROJECT_ROOT"
  5. Clean up the temp file.

Every active reviewer's stamp lands in <project>/reviews/INDEX.md with the same orchestrator name and roughly the same Last Run timestamp, making the cluster visible at a glance. With --clarity, this includes the fifth clarity-reviewer row.

Why the orchestrator stamps (not the sub-agent)

Agents have inconsistent Bash tool grants at runtime (the 2026-05-19 harness investigation showed paper-critic and domain-reviewer self-report Bash unavailable despite YAML grants). The orchestrator always has Bash and always runs after the agents return. Moving stamping here decouples it from agent tool-surface uncertainty.

Schema: the installed shared resource shared/review-state-schema.md. Stamp directive format: the installed shared resource _shared/stamp-directive-spec.md.

Anti-Patterns

  • Don't include referee2-reviewer in the cluster — that's the final-stage hostile review, not mid-draft.
  • Don't run cluster review on a broken build — phase-1 check should abort.
  • Don't auto-apply fixes from the synthesised report — the report is read-only output. User reviews and dispatches edit-agents (per subagent-write-guard.md) separately.
  • Don't run cluster review on every save — designed for milestone-driven iteration, not continuous integration.

© flonat, 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 skills/review-cluster of flonat/flonat-research.

Open the folder on GitHubat commit da27600

Compare with similar skills

Review Cluster 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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Questions about Review Cluster

What does Review Cluster do?

Deliver a mid-draft adversarial review of a paper — runs paper-critic + domain-reviewer + claim-verify + blindspot in parallel, optionally adds clarity-reviewer, then auto-synthesises into a…. Review Cluster is an agent skill from flonat/flonat-research. Deliver a mid-draft adversarial review of a paper — runs paper-critic + domain-reviewer + claim-verify + blindspot in parallel, optionally adds clarity-reviewer, then auto-synthesises into a prioritised revision plan.

When should I use Review Cluster?

Review Cluster fits situations like: the user requests a mid-draft adversarial review of a paper — runs paper-critic + domain-reviewer + claim-verify + blindspot in parallel; optionally adds clarity-reviewer; then auto-synthesises into a prioritised revision plan.

How do I install Review Cluster in Claude Code?

Run `npx skills add flonat/flonat-research --skill review-cluster -a claude-code`. Or copy the skill folder (skills/review-cluster in flonat/flonat-research) into .claude/skills/review-cluster in your project. Claude Code loads it when a task matches its description.

How do I install Review Cluster in Codex?

Run `npx skills add flonat/flonat-research --skill review-cluster -a codex`. Or copy the skill folder (skills/review-cluster in flonat/flonat-research) into .agents/skills/review-cluster in your project. Codex loads it when a task matches its description.

Can I use Review Cluster 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 flonat/flonat-research --skill review-cluster -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/review-cluster, .gemini/skills/review-cluster, .github/skills/review-cluster and .opencode/skills/review-cluster in your project.

What does Review Cluster need to run?

Going by SKILL.md and its folder, Review Cluster needs the command-line tools its instructions call (bash). Its frontmatter pre-approves these tools: Read, Glob, Grep, Bash(uv*), Bash(ls*), Bash(git*), Task, Skill, AskUserQuestion.

Does Review Cluster 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 Review Cluster 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 Review Cluster use?

Review Cluster 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 Review Cluster use?

About 4.9k tokens (SKILL.md is roughly 20k 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 Review Cluster?

Skills that share tags, products or a category with Review Cluster: Vector Cluster (ruvnet/ruflo, 74k stars), Criticism Self Criticism (HughYau/qiushi-skill, 3.8k stars), Crossframe Critical (sickn33/agentic-awesome-skills, 47k stars) and Critical Images (thedaviddias/Front-End-Checklist, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Review Cluster?

flonat (a GitHub user) maintains it in flonat/flonat-research, which has 146 GitHub stars. The repository holds 83 skills in this directory. The repository was last updated on September 29, 2026.

Source: flonat/flonat-research on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.