research-loom-review
Use when auditing a research manuscript for supported claims, citation correctness, venue readiness, or responding to reviewers.
Skill by amaljithkuttamath
Chalk Labs
Need help deploying research-loom-review?
Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/amaljithkuttamath-research-loom-review
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Use cases: research
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md and code. Checked Nov 1, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/research-loom-review
What's inside
- Skill name
research-loom-review- Description
- Use when auditing a research manuscript for supported claims, citation correctness, venue readiness, or responding to reviewers.
- License
- MIT
- Instructions
- 11 lines in SKILL.md · view on GitHub
Files (3)
- SKILL.md
- openai.yaml · agents/
- research-and-review.md · references/
SKILL.md (first lines)
# Research Review Read manuscript, source ledger, actual research records, and [references/research-and-review.md](references/research-and-review.md). Verify alignment of question, methods, results, and conclusion; important quantitative/causal claims; citation-reference consistency; source support; uncertainty/limitations; and figure/table agreement. For reviewer comments, produce a comment-to-change matrix with action, manuscript location, evidence, response, and unresolved issue. Make justified requested revisions; do not describe unperformed work as completed. Verify current venue requirements before claiming readiness. Report completed checks, unresolved gaps, and unverified requirements. Route evidence gaps to search planning and prose/analysis corrections to the relevant stage. Return a prioritized review or revised manuscript as requested; do not submit or contact others without explicit authorization. When invoked by Research Loom, return paper/search/claim records matching [the shared paper data contract](../research-loom/references/paper-data.md). The orchestrator merges and validates them.
From amaljithkuttamath/research-loom, MIT.
More from amaljithkuttamath/research-loom
- 0.592score
research-loom
amaljithkuttamath
Use when running a configurable research workflow graph with selectable stage skills, multiple search branches, and persistent project context.
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
research-loom-synthesize
amaljithkuttamath
Use when combining research search branches into an evidence synthesis with traceable claims, disagreements, and remaining gaps.
SkillAFreshness: A★ 1Claude Code +9 - 0.586score
research-loom-draft
amaljithkuttamath
Use when drafting research-paper sections from an evidence-linked outline and actual research records.
SkillAFreshness: A★ 1Claude Code +9 - 0.586score
research-loom-search
amaljithkuttamath
Use when executing a planned research search branch and recording verifiable sources and search provenance.
SkillAFreshness: A★ 1Claude Code +9 - 0.584score
research-loom-eval
amaljithkuttamath
Use before shipping Research Loom skills or changing their graph, project memory, search provenance, or paper data contracts.
SkillAFreshness: A★ 1Claude Code +9 - 0.582score
research-loom-search-plan
amaljithkuttamath
Use when designing source-specific research queries and multiple search branches for a focused question or several research goals.
SkillAFreshness: A★ 1Claude Code +9 - 0.582score
research-loom-interview
amaljithkuttamath
Use when interviewing a user to understand a research topic, motivation, goals, and constraints before narrowing the question.
SkillAFreshness: A★ 1Claude Code +9 - 0.581score
research-loom-outline
amaljithkuttamath
Use when building an academic paper outline from an agreed research question and evidence synthesis.
SkillAFreshness: A★ 1Claude Code +9 - 0.581score
research-loom-narrow
amaljithkuttamath
Use when turning a broad research topic or several goals into focused, searchable research questions.
SkillAFreshness: A★ 1Claude Code +9
Signals
- Stars
- 1
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Oct 4, 2026 (1 month ago)
- Last release
- Oct 4, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from amaljithkuttamath
- 0.592score
research-loom
amaljithkuttamath
Use when running a configurable research workflow graph with selectable stage skills, multiple search branches, and persistent project context.
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
research-loom-synthesize
amaljithkuttamath
Use when combining research search branches into an evidence synthesis with traceable claims, disagreements, and remaining gaps.
SkillAFreshness: A★ 1Claude Code +9 - 0.586score
research-loom-draft
amaljithkuttamath
Use when drafting research-paper sections from an evidence-linked outline and actual research records.
SkillAFreshness: A★ 1Claude Code +9 - 0.586score
research-loom-search
amaljithkuttamath
Use when executing a planned research search branch and recording verifiable sources and search provenance.
SkillAFreshness: A★ 1Claude Code +9 - 0.584score
research-loom-eval
amaljithkuttamath
Use before shipping Research Loom skills or changing their graph, project memory, search provenance, or paper data contracts.
SkillAFreshness: A★ 1Claude Code +9 - 0.582score
research-loom-interview
amaljithkuttamath
Use when interviewing a user to understand a research topic, motivation, goals, and constraints before narrowing the question.
SkillAFreshness: A★ 1Claude Code +9
Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
Get research-loom-review running in your business
Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.
Cite this page
research-loom-review skill. Agent Mart. https://agentmart.dev/skills/amaljithkuttamath-research-loom-review (last updated 2026-10-24)