Agent skill

Synthesise Reviews

by flonat in flonat/flonat-research

Deduplicate and reconcile multiple completed review reports into one prioritised revision plan with conflicts and dependencies made explicit.

MITAuto-check passed

Install Synthesise Reviews

skills CLI
$ npx skills add flonat/flonat-research --skill synthesise-reviews -a claude-code

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

GitHub CLI
$ gh skill install flonat/flonat-research synthesise-reviews --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/synthesise-reviews .claude/skills/synthesise-reviews && 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
synthesise-reviews
GitHub stars
146
Token cost
~2.3k tokens
SKILL.md length
914 words
Files
1
Skills in repo
83
Repo updated
First seen
Licence
MIT

At a glance

Deduplicate and reconcile multiple completed review reports into one prioritised revision plan with conflicts and dependencies made explicit.

  • Works in 7 steps: Discover Reports → Parse Issues → 5: Spot-verify findings against their… → …
  • Parallel reviewers have returned findings that need a single action sequence
  • SKILL.md covers Output Path, Purpose, When to Use and When NOT to Use, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Synthesise Reviews is an agent skill from flonat/flonat-research. Deduplicate and reconcile multiple completed review reports into one prioritised revision plan with conflicts and dependencies made explicit. Use when parallel reviewers have returned findings that need a single action sequence. Not for running the reviews; use $review-cluster.

Its SKILL.md is about 2.3k 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

  • Parallel reviewers have returned findings that need a single action sequence

Example prompts

  • “/synthesise-reviews”

Requirements

  • Pre-approved tools (allowed-tools): Read, Glob, Grep, Write, Edit, AskUserQuestion

Workflow steps

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

  1. Discover Reports
  2. Parse Issues
  3. 5: Spot-verify findings against their cited location (integrity gate)
  4. Cross-Reference and Consensus Escalation
  5. Group into Workstreams
  6. Output Synthesis Report
  7. Optionally Hand Off to Internal Strategic Revision

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
    • Write
    • Edit
    • AskUserQuestion

    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 markdown).

    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

Synthesise Reviews loads about 2.3k tokens when it runs. Until then it costs about 74 tokens; SKILL.md has 914 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~74
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k

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). 914 words, ~2,298 tokens.

Download SKILL.mdSave it as .claude/skills/synthesise-reviews/SKILL.md (or your agent's skills folder).
name
synthesise-reviews
description
Deduplicate and reconcile multiple completed review reports into one prioritised revision plan with conflicts and dependencies made explicit. Use when parallel reviewers have returned findings that need a single action sequence. Not for running the reviews; use $review-cluster.
allowed-tools
Read, Glob, Grep, Write, Edit, AskUserQuestion
argument-hint
[optional: path to reviews/ directory]

Synthesise Reviews

Combine multiple review reports into a single prioritised revision plan with cross-reviewer consensus ranking.

Output Path

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

  • Source slug: synthesise-reviews
  • Write reports to: reviews/<scope>/synthesise-reviews/YYYY-MM-DD-HHMM.md inside the project, where <scope> is the paper slug (e.g. paper-jtp) or _project for project-level synthesis. 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 update: if reviews/INDEX.md exists, write a one-line entry under "Latest per source" pointing at the new file. Otherwise review-recap will rebuild the index next time it runs.
  • Infrastructure repos (Task-Management, atlas-workspace, etc.): this section does not apply — the path-scoped rule won't load there.

Purpose

After running parallel review agents (paper-critic, domain-reviewer, referee2-reviewer), this skill reads their internal reports, cross-references issues, and produces a unified synthesis grouped into workstreams by priority and theme. It decides the consolidated issue set; strategic-revision --internal is the separate step that turns a complex issue set into an executable DAG.

Inspired by APE Papers' reviewer_response_plan_1.md pattern — workstreams grouped by priority, each concern traced to its reviewer.

When to Use

  • After running 2+ review agents on a paper
  • After a council review round
  • When preparing a revision plan from multiple feedback sources
  • Before an optional strategic-revision --internal handoff when the consolidated issues are interdependent

When NOT to Use

  • Before reviews exist — run the review agents first
  • To run reviews — use the individual agents (paper-critic, domain-reviewer, referee2-reviewer)
  • For a single review — just read the report directly
  • For genuine venue referee reports or an R&R response — use strategic-revision --external

Workflow

Step 1: Discover Reports

Glob for review files in the project root. Scan the new canonical structure first, then fall back to legacy:

reviews/<scope>/<check>/YYYY-MM-DD*.md (canonical: e.g. reviews/paper-jtp/paper-critic/2026-06-28-1437.md)
reviews/<check>/YYYY-MM-DD*.md (legacy: e.g. reviews/paper-critic/2026-06-28-1437.md)

Where <scope> is a paper slug (e.g. paper-jtp) or _project.

If no reports found, ask the user where the reports are.

Present the discovered reports and their dates. If reports are from different dates, ask whether to synthesise all or just the most recent round.

Step 2: Parse Issues

For each report, extract the issue list:

From paper-critic CRITIC-REPORT.md:

  • Parse the Deductions table (columns: #, Issue, Tier, Deduction, Category, Location)
  • Extract Critical (C*), Major (M*), Minor (m*) issue details from the detailed sections

From domain-reviewer DOMAIN-REVIEW.md:

  • Parse each Lens section's issue table (columns: #, Issue, Severity, Location)
  • Map: CRITICAL → Critical, MAJOR → Major, MINOR → Minor

From referee2-reviewer REFEREE2-REPORT.md:

  • Parse the structured findings from each audit dimension
  • Extract severity-tagged issues
Step 2.5: Spot-verify findings against their cited location (integrity gate)

Per _shared/audit-integrity.md Rule 2, a review sub-agent's finding is not trusted until its evidence is confirmed — reviewers can emit plausible findings with a fabricated path:line. Before synthesising, spot-verify a random sample of the parsed issues (≥3, or 20% — whichever is larger, weighted toward Critical/Major):

  1. For each sampled issue, open its cited Location (path:line) and confirm the quoted text/code is actually there and the issue follows from it.
  2. Any sample miss (cited line doesn't exist, quote isn't there, or the claim doesn't follow) ⇒ that report is suspect: widen the check to all of that reviewer's findings and drop every one that can't be grounded.
  3. Findings with no Location/quotable anchor at all are dropped, not synthesised — a finding you cannot point at is inadmissible.

Record a one-line Integrity: N sampled, M dropped note in the synthesis output. If reports lack locations entirely and nothing can be verified, say so rather than silently trusting them.

Show full SKILL.md (330 more words)Show less
Step 3: Cross-Reference and Consensus Escalation

Match issues across reports by semantic similarity (same underlying problem, possibly described differently):

ConsensusPriority
Flagged by 3/3 reviewersCritical (regardless of individual severity)
Flagged by 2/3 reviewersMajor (or higher if any reviewer rated Critical)
Flagged by 1/3 reviewersKeep original severity

Important: Consensus can only escalate severity, never reduce it. If one reviewer says Critical and two say Minor, it stays Critical.

Step 4: Group into Workstreams

Cluster issues by theme:

ThemeWhat belongs here
Identification & MethodologyResearch design, estimation strategy, assumptions, causal claims
Mathematical RigourDerivations, proofs, notation consistency, formal claims
Empirical AnalysisData, results, robustness, replication
Literature & PositioningCitations, positioning, literature gaps, framing
Presentation & StructureWriting quality, organisation, clarity, flow
Technical (LaTeX)Compilation, references, formatting, figures, tables

Within each workstream, sort by priority (Critical → Major → Minor).

Step 5: Output Synthesis Report

Write to reviews/<scope>/synthesise-reviews/YYYY-MM-DD-HHMM.md in the project, where <scope> is the paper slug (e.g. paper-jtp) or _project for project-level synthesis. This report contains the consolidated revision plan synthesised from all input reports.

markdown
# Revision Plan

**Date:** YYYY-MM-DD
**Reports synthesised:** [list of report files with dates]
**Total issues:** N (C: X, M: Y, m: Z)

## Positive Consensus

Issues/strengths noted positively by multiple reviewers:

- [Strength 1] — noted by [reviewers]
- [Strength 2] — noted by [reviewers]

## Workstream 1: [Theme Name]

| # | Priority | Issue | Flagged by | Action | Source |
|---|----------|-------|------------|--------|--------|
| 1 | Critical | [description] | paper-critic (C1), domain-reviewer (A2), referee2 | [suggested action] | [file:line] |
| 2 | Major | [description] | paper-critic (M3), domain-reviewer (D1) | [suggested action] | [file:line] |
| 3 | Minor | [description] | paper-critic (m2) | [suggested action] | [file:line] |

## Workstream 2: [Theme Name]

[Same table format]

...

## Summary

| Workstream | Critical | Major | Minor | Total |
|------------|----------|-------|-------|-------|
| Identification & Methodology | X | Y | Z | N |
| Mathematical Rigour | X | Y | Z | N |
| ... | | | | |
| **Total** | **X** | **Y** | **Z** | **N** |

## Recommended Order

1. [First workstream to tackle and why]
2. [Second workstream]
3. ...

## Consensus Statistics

- Issues confirmed by all reviewers: N
- Issues confirmed by majority (2/3): N
- Issues from single reviewer: N
- Total unique issues: N
Step 6: Optionally Hand Off to Internal Strategic Revision

If the synthesis contains multiple blocking or interdependent workstreams, offer strategic-revision --internal <synthesis-path>. That skill creates the executable task DAG and retains this synthesis as a source in its manifest. Do not invoke it when a ranked synthesis is sufficient.

Never generate a venue response letter from internal review material. Genuine referee comments and rebuttal scaffolds belong to strategic-revision --external and remain under the venue correspondence package.

Anti-Patterns

  • Do NOT run reviews — only synthesise existing reports
  • Do NOT modify source reports — they are read-only inputs
  • Do NOT escalate severity beyond consensus rules — if only one reviewer flagged something, keep their severity unless it's confirmed by others
  • Do NOT invent issues — only report what the reviewers found
  • Do NOT merge issues that are genuinely different — only merge when the same underlying problem is described differently
  • Do NOT produce venue correspondence or response letters — this skill consolidates internal review evidence only

© 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/synthesise-reviews of flonat/flonat-research.

Open the folder on GitHubat commit da27600

Compare with similar skills

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Questions about Synthesise Reviews

What does Synthesise Reviews do?

Deduplicate and reconcile multiple completed review reports into one prioritised revision plan with conflicts and dependencies made explicit. Synthesise Reviews is an agent skill from flonat/flonat-research. Deduplicate and reconcile multiple completed review reports into one prioritised revision plan with conflicts and dependencies made explicit.

When should I use Synthesise Reviews?

Synthesise Reviews fits situations like: parallel reviewers have returned findings that need a single action sequence.

How do I install Synthesise Reviews in Claude Code?

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

How do I install Synthesise Reviews in Codex?

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

Can I use Synthesise Reviews 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 synthesise-reviews -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/synthesise-reviews, .gemini/skills/synthesise-reviews, .github/skills/synthesise-reviews and .opencode/skills/synthesise-reviews in your project.

What does Synthesise Reviews need to run?

SKILL.md names no scripts, command-line tools or credentials: Synthesise Reviews is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Glob, Grep, Write, Edit, AskUserQuestion.

Does Synthesise Reviews 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 Synthesise Reviews 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 Synthesise Reviews use?

Synthesise Reviews 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 Synthesise Reviews use?

About 2.3k tokens (SKILL.md is roughly 9.2k 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 Synthesise Reviews?

Skills that share tags, products or a category with Synthesise Reviews: Verification Before Completion (foryourhealth111-pixel/Vibe-Skills, 3.6k stars), Verification Before Completion (farm-fe/farm, 5.6k stars), Verification Before Completion (jnMetaCode/superpowers-zh, 8.3k stars) and Issues Deduplication (JetBrains/ideavim, 10k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Synthesise Reviews?

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.