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Agent skill

Research Quality Review

by grandamenium in grandamenium/cortextos

Audit source quality, scoring performance, duplicate patterns, source failures, stale config, and tuning opportunities.

MITAuto-check passed

Install Research Quality Review

skills CLI
$ npx skills add grandamenium/cortextos --skill research-quality-review -a claude-code

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

GitHub CLI
$ gh skill install grandamenium/cortextos research-quality-review --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/grandamenium/cortextos.git skills-src && mkdir -p .claude/skills && cp -r skills-src/community/agents/research-agent/.claude/skills/research-quality-review .claude/skills/research-quality-review && 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
research-quality-review
GitHub stars
101
Token cost
~446 tokens
SKILL.md length
132 words
Files
1
Skills in repo
55
Repo updated
First seen
Licence
MIT

At a glance

Audit source quality, scoring performance, duplicate patterns, source failures, stale config, and tuning opportunities.

  • Works in 6 steps: Source failures → Source quality → Scoring quality → …
  • SKILL.md covers Inputs, Review Checklist and Output
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Research Quality Review is an agent skill from grandamenium/cortextos. Audit source quality, scoring performance, duplicate patterns, source failures, stale config, and tuning opportunities.

Its SKILL.md is about 450 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The licence is MIT.

Example prompts

  • “/research-quality-review”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Source failures
  2. Source quality
  3. Scoring quality
  4. Deduplication
  5. Delivery quality
  6. Topic briefing quality

What it can do on your machine

Read from SKILL.md and the folder at commit 6f93838. 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 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

Research Quality Review loads about 446 tokens when it runs. Until then it costs about 36 tokens; SKILL.md has 132 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~36
When it runs · the whole SKILL.md, loaded when a task matches
~446

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 grandamenium/cortextos at commit 6f93838, republished under its MIT licence (© grandamenium). 132 words, ~446 tokens.

Download SKILL.mdSave it as .claude/skills/research-quality-review/SKILL.md (or your agent's skills folder).
name
research-quality-review
description
Audit source quality, scoring performance, duplicate patterns, source failures, stale config, and tuning opportunities.

Research Quality Review

Run weekly, after a few research cycles, or whenever the briefs feel noisy.

Inputs

  • research/output/
  • research/topic-briefings/
  • research/sources.json
  • research/scoring-rubric.json
  • research/db/signals.db if available
  • recent user feedback

Review Checklist

  1. Source failures:
    • repeated timeouts
    • rate limits
    • empty sources
    • auth failures
  2. Source quality:
    • high-volume low-signal sources
    • sources that never produce selected items
    • missing source categories
  3. Scoring quality:
    • obvious good signals below threshold
    • noisy signals above threshold
    • over-weighted platform bonuses
    • stale or too-broad keywords
  4. Deduplication:
    • repeated same story across platforms
    • old items resurfacing without new evidence
  5. Delivery quality:
    • too much detail in summaries
    • weak source attribution
    • unclear recommended actions
  6. Topic briefing quality:
    • options too similar
    • low evidence topics
    • weak why-now framing

Output

Write:

text
research/output/YYYY-MM-DD/research-quality-review.md

Use this format:

markdown
# Research Quality Review -- YYYY-MM-DD

## Summary
[What is working / not working.]

## Source Changes Recommended
- Keep:
- Add:
- Remove:
- Watch:

## Scoring Changes Recommended
- [Specific rubric edit and why]

## Workflow Changes Recommended
- [Cron, delivery, topic briefing, output format changes]

## Human Decisions Needed
- [Decision and tradeoff]

Do not edit source/scoring config automatically unless the user asks. Propose changes first.

© grandamenium, 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 community/agents/research-agent/.claude/skills/research-quality-review of grandamenium/cortextos.

Open the folder on GitHubat commit 6f93838

Compare with similar skills

Research Quality Review 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.

Research Quality Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Research Quality Review this skillgrandamenium/cortextos101—~446Automated safety check: PassMIT
Claw Scoreopenclaw/openclaw392k—~2.5kAutomated safety check: PassMIT
Tag Duplicate PRs Issuesopenclaw/openclaw392k—~4kAutomated safety check: PassMIT
Harness Scoreruvnet/ruflo74k—~605Automated safety check: NotesMIT
Duplicate JSthedaviddias/Front-End-Checklist74k—~423Automated safety check: PassMIT
Score Evalsickn33/agentic-awesome-skills47k1 repos~304Automated safety check: PassMIT

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Questions about Research Quality Review

What does Research Quality Review do?

Audit source quality, scoring performance, duplicate patterns, source failures, stale config, and tuning opportunities. Research Quality Review is an agent skill from grandamenium/cortextos. Audit source quality, scoring performance, duplicate patterns, source failures, stale config, and tuning opportunities.

How do I install Research Quality Review in Claude Code?

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

How do I install Research Quality Review in Codex?

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

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

What does Research Quality Review need to run?

SKILL.md names no scripts, command-line tools or credentials: Research Quality Review is instructions for the agent only.

Does Research Quality Review 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 Research Quality Review 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 Research Quality Review use?

Research Quality Review 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 Research Quality Review use?

About 446 tokens (SKILL.md is roughly 1.8k 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 Research Quality Review?

Skills that share tags, products or a category with Research Quality Review: Claw Score (openclaw/openclaw, 392k stars), Tag Duplicate PRs Issues (openclaw/openclaw, 392k stars), Harness Score (ruvnet/ruflo, 74k stars) and Duplicate JS (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 Research Quality Review?

grandamenium (a GitHub user) maintains it in grandamenium/cortextos, which has 101 GitHub stars. The repository holds 55 skills in this directory. The repository was last updated on September 23, 2026.

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