Offers
Nexus-JPF/note-companion
When the user wants to design, construct, or improve an offer — the thing they actually sell — including value framing, bonus stacking, guarantee design, scarcity/urgency, naming, and payment…
Scrape G2, Capterra, and Trustpilot reviews for your product and competitors, then extract recurring themes, objections, proof points, and exact customer language for use in messaging.
Install Review Intelligence Digest
$ npx skills add gooseworks-ai/goose-skills --skill review-intelligence-digest -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install gooseworks-ai/goose-skills review-intelligence-digest --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/gooseworks-ai/goose-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/research/composites/review-intelligence-digest .claude/skills/review-intelligence-digest && 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 "review-intelligence-digest" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/research/composites/review-intelligence-digest into .claude/skills/review-intelligence-digest/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-intelligence-digest", 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/gooseworks-ai/goose-skills/tree/main/skills/research/composites/review-intelligence-digestType 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 gooseworks-ai/goose-skills --skill review-intelligence-digest -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install gooseworks-ai/goose-skills review-intelligence-digest --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/research/composites/review-intelligence-digest .agents/skills/review-intelligence-digest && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "review-intelligence-digest" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/research/composites/review-intelligence-digest into .agents/skills/review-intelligence-digest/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-intelligence-digest", 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 gooseworks-ai/goose-skills --skill review-intelligence-digest -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install gooseworks-ai/goose-skills review-intelligence-digest --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/research/composites/review-intelligence-digest .cursor/skills/review-intelligence-digest && 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 "review-intelligence-digest" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/research/composites/review-intelligence-digest into .cursor/skills/review-intelligence-digest/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-intelligence-digest", 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/gooseworks-ai/goose-skills.git --path skills/research/composites/review-intelligence-digest--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 gooseworks-ai/goose-skills --skill review-intelligence-digest -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install gooseworks-ai/goose-skills review-intelligence-digest --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/research/composites/review-intelligence-digest .gemini/skills/review-intelligence-digest && 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 "review-intelligence-digest" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/research/composites/review-intelligence-digest into .gemini/skills/review-intelligence-digest/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-intelligence-digest", 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 gooseworks-ai/goose-skills review-intelligence-digestInstalls 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 gooseworks-ai/goose-skills --skill review-intelligence-digest -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/research/composites/review-intelligence-digest .github/skills/review-intelligence-digest && 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 "review-intelligence-digest" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/research/composites/review-intelligence-digest into .github/skills/review-intelligence-digest/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-intelligence-digest", 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 gooseworks-ai/goose-skills --skill review-intelligence-digest -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install gooseworks-ai/goose-skills review-intelligence-digest --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/research/composites/review-intelligence-digest .opencode/skills/review-intelligence-digest && 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 "review-intelligence-digest" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/research/composites/review-intelligence-digest into .opencode/skills/review-intelligence-digest/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-intelligence-digest", 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.
Facts
- Skill name
review-intelligence-digest- GitHub stars
- 1.2k
- Used in
- 1 other repo
- Token cost
- ~1.7k tokens
- SKILL.md length
- 529 words
- Files
- 2
- Skills in repo
- 273
- Repo updated
- First seen
- Licence
- MIT
At a glance
Scrape G2, Capterra, and Trustpilot reviews for your product and competitors, then extract recurring themes, objections, proof points, and exact customer language for use in messaging.
- Works in 4 steps: Intake → Scrape Reviews → Categorize & Cluster → …
- A marketing team needs to ground messaging in real customer language
- SKILL.md covers When to Use, Phase 0: Intake, Phase 1: Scrape Reviews and Phase 2: Categorize & Cluster, plus 5 more sections
- Calls python3; needs APIFY_API_TOKEN
What it does
Review Intelligence Digest is an agent skill from gooseworks-ai/goose-skills. Scrape G2, Capterra, and Trustpilot reviews for your product and competitors, then extract recurring themes, objections, proof points, and exact customer language for use in messaging. Chains review-site-scraper with LLM analysis. Produces a weekly or monthly digest that feeds directly into copywriting, positioning, and sales enablement. Use when a marketing team needs to ground messaging in real customer language.
Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `skill.meta.json`).
It sits in Sales & Support, covering Web scraping, Copywriting and Customer feedback analysis. The repository describes itself as: Library of Growth & GTM skills + data APIs for Claude Code, Codex, Cursor to run ads, social, content, lead gen, seo and data scraping. The licence is MIT.
When your agent uses it
- A marketing team needs to ground messaging in real customer language
- Tasks that involve Web scraping
- Tasks that involve Copywriting
Example prompts
- “/review-intelligence-digest”
Requirements
- Python 3
- A credential in APIFY_API_TOKEN
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit c650c6d. 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
Shell commands in SKILL.md call:
python3
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 these keys or tokens, usually read from environment variables:
APIFY_API_TOKEN
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Review Intelligence Digest loads about 1.7k tokens when it runs. Until then it costs about 111 tokens; SKILL.md has 529 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.
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 gooseworks-ai/goose-skills at commit c650c6d, republished under its MIT licence (© gooseworks-ai). 529 words, ~1,732 tokens.
Download SKILL.mdSave it as
.claude/skills/review-intelligence-digest/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- review-intelligence-digest
- description
- Scrape G2, Capterra, and Trustpilot reviews for your product and competitors, then extract recurring themes, objections, proof points, and exact customer language for use in messaging. Chains review-site-scraper with LLM analysis. Produces a weekly or monthly digest that feeds directly into copywriting, positioning, and sales enablement. Use when a marketing team needs to ground messaging in real customer language.
- tags
- research
Review Intelligence Digest
Scrape reviews for your product and top competitors, then extract what actually matters for marketing: the exact language customers use, recurring pain points, proof points that convert, and objections to pre-empt.
Core principle: Your best marketing copy is already written — by your customers, in their reviews. This skill surfaces it.
When to Use
- "What are customers saying about us vs competitors?"
- "Find proof points and objections from our G2 reviews"
- "What language do our customers use to describe the problem we solve?"
- "Run a review audit for [client]"
- "What are [competitor]'s customers complaining about?"
Phase 0: Intake
- Your product name + review page URLs (G2, Capterra, Trustpilot — any/all)
- Competitor names + their review page URLs (1-3 competitors recommended)
- What are you trying to learn? (Pick primary focus or do all):
- Messaging mining — extract ICP language and proof points
- Competitive displacement — find competitor pain points to exploit
- Objection mapping — identify what's stopping people from buying/staying
- Feature gaps — what do customers wish existed?
- Time range: last 3 months (default), last 6 months, or all time?
Phase 1: Scrape Reviews
Run review-site-scraper for your product and each competitor:
# Your product
python3 skills/capabilities/review-site-scraper/scripts/scrape_reviews.py \
--platform g2 \
--url "<your_g2_url>" \
--days 90 \
--output json
# Competitor
python3 skills/capabilities/review-site-scraper/scripts/scrape_reviews.py \
--platform g2 \
--url "<competitor_g2_url>" \
--days 90 \
--output jsonRepeat for Capterra and Trustpilot as needed.
Collect for each review: rating (1-5), title, body text, pros, cons, reviewer role/company (if available), date.
Phase 2: Categorize & Cluster
Analyze all reviews through these five lenses:
Lens 1: Proof Points (5-star reviews)
Extract specific outcomes and metrics customers mention:
- Time saved / speed improvements
- Revenue or pipeline impact
- Headcount equivalent replaced
- Process improvements
- Before/after comparisons
Flag reviews with numbers — these are the highest-value proof points.
Lens 2: Core Pain Language
What words and phrases do customers use to describe the problem they had before using the product? This is gold for cold email hooks and ad copy.
Patterns to extract:
- "Before [product], we were..."
- "We used to [manual process]..."
- "The biggest frustration was..."
- "We couldn't [thing] until..."
Show full SKILL.md (215 more words)Show less
Lens 3: Objection Mapping (3-4 star reviews, negative cons)
What do customers wish was different? What almost stopped them from buying?
- Price/value concerns
- Onboarding friction
- Missing features
- Integration issues
- Support quality
Group by theme. Count frequency.
Lens 4: Competitive Displacement Signals (competitor reviews)
In competitor reviews, look for:
- Specific pain points your product doesn't have
- Features they're missing that you offer
- Complaints about price, support, or reliability
- Mentions of switching ("we switched to X")
These are your competitive displacement angles.
Lens 5: Buyer Language Patterns
How do customers categorize and search for your type of product?
- What category words do they use?
- What comparison phrases appear? (e.g., "compared to Salesforce", "vs HubSpot")
- What role/title wrote the reviews? (validates ICP)
Phase 3: Output Format
# Review Intelligence Digest — [DATE]
Products analyzed: [your product], [competitors]
Reviews analyzed: [N] total | Period: [date range]
---
## Proof Points Library (use in copy directly)
### With Metrics (highest value)
- "[Exact quote with number]" — [Reviewer role], [Platform], [Date]
- "[Exact quote with number]" — ...
### Process/Experience Wins
- "[Exact quote]" — [Reviewer role], [Platform]
- ...
---
## Customer Pain Language
Words and phrases customers use to describe the problem you solve:
**Verbatim phrases (use in hooks and subject lines):**
- "[Exact phrase]" (appeared in [N] reviews)
- "[Exact phrase]" (appeared in [N] reviews)
- ...
**Paraphrased themes:**
1. [Theme] — [N] reviews mention this | Example: "[quote]"
2. [Theme] — ...
---
## Objection Map
| Objection | Frequency | Verbatim example | How to address |
|-----------|-----------|-----------------|----------------|
| [Objection] | [N] reviews | "[quote]" | [suggested response] |
| ... | | | |
---
## Competitive Displacement Intel
### [Competitor Name]
**Top complaints (use as outreach hooks):**
1. [Complaint] — "[Verbatim quote]" | Appeared [N] times
2. ...
**What their customers want that we offer:**
- [Feature/capability] — "[review evidence]"
**Suggested displacement angle:**
> "[Pitch sentence targeting their unhappy customers]"
---
## SEO / Messaging Vocabulary
Words and phrases to incorporate in website copy, ads, and content:
**High-frequency ICP vocabulary:**
- "[word/phrase]" — used in [N] reviews
- ...
**Category comparison terms:**
- Customers compare you to: [list]
- Customers search for: [list]
---
## Recommended Actions
### Immediate (use this week)
1. Add "[proof point quote]" to homepage or outbound sequences
2. Address "[top objection]" in onboarding flow or sales deck
3. Use "[pain phrase]" as hook in next cold email batch
### Strategic
1. [Feature gap mentioned in reviews — prioritize or address in messaging]
2. [Competitive weakness to build a campaign around]Save to review-digest-[YYYY-MM-DD].md in the current working directory.
Scheduling
Run monthly (reviews don't change fast enough to warrant weekly):
0 8 1 * * python3 run_skill.py review-intelligence-digest --client <client-name>Cost
| Component | Cost |
|---|---|
| G2 reviews (per product) | Free tier available (Apify) |
| Capterra reviews (per product) | ~$0.20-0.50 (Apify, pay-per-result) |
| Trustpilot reviews (per product) | ~$0.20/1k reviews |
| Total per monthly run (you + 2 competitors) | ~$1-3 |
Tools Required
- Apify API token —
APIFY_API_TOKENenv var - Upstream skill:
review-site-scraper
Trigger Phrases
- "Mine our reviews for proof points and messaging"
- "What are [competitor]'s customers complaining about?"
- "Run review intelligence for [client]"
- "Give me customer language I can use in copy"
© gooseworks-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 1 other file in skills/research/composites/review-intelligence-digest of gooseworks-ai/goose-skills.
- SKILL.md
- skill.meta.json
Open the folder on GitHubat commit c650c6d
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in gooseworks-ai/goose-skills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Review Intelligence Digest 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 |
|---|---|---|---|---|---|---|
| Review Intelligence Digest this skillgooseworks-ai/goose-skills | 1.2k | 1 repos | ~1.7k | Automated safety check: Pass | MIT | |
| OffersNexus-JPF/note-companion | 870 | 2 repos | ~2.3k | Automated safety check: Pass | MIT | |
| Google Maps Reviews Scrapergmapsscraper/google-maps-agent-skills | 132 | — | ~1.2k | Automated safety check: Pass | MIT | |
| Amazon Reviews Extractorbrowser-act/skills | 6.1k | 1 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Outreach Manageraaron-he-zhu/aaron-marketing-skills | 2.9k | 1 repos | ~5.4k | Automated safety check: Pass | Apache-2.0 | |
| Etsy Product Detailbrowser-act/skills | 6.1k | — | ~2.3k | Automated safety check: Pass | MIT |
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Related
Questions about Review Intelligence Digest
What does Review Intelligence Digest do?
Scrape G2, Capterra, and Trustpilot reviews for your product and competitors, then extract recurring themes, objections, proof points, and exact customer language for use in messaging. Review Intelligence Digest is an agent skill from gooseworks-ai/goose-skills. Scrape G2, Capterra, and Trustpilot reviews for your product and competitors, then extract recurring themes, objections, proof points, and exact customer language for use in messaging.
When should I use Review Intelligence Digest?
Review Intelligence Digest fits situations like: A marketing team needs to ground messaging in real customer language; tasks that involve Web scraping; tasks that involve Copywriting.
How do I install Review Intelligence Digest in Claude Code?
Run `npx skills add gooseworks-ai/goose-skills --skill review-intelligence-digest -a claude-code`. Or copy the skill folder (skills/research/composites/review-intelligence-digest in gooseworks-ai/goose-skills) into .claude/skills/review-intelligence-digest in your project. Claude Code loads it when a task matches its description.
How do I install Review Intelligence Digest in Codex?
Run `npx skills add gooseworks-ai/goose-skills --skill review-intelligence-digest -a codex`. Or copy the skill folder (skills/research/composites/review-intelligence-digest in gooseworks-ai/goose-skills) into .agents/skills/review-intelligence-digest in your project. Codex loads it when a task matches its description.
Can I use Review Intelligence Digest 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 gooseworks-ai/goose-skills --skill review-intelligence-digest -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-intelligence-digest, .gemini/skills/review-intelligence-digest, .github/skills/review-intelligence-digest and .opencode/skills/review-intelligence-digest in your project.
What does Review Intelligence Digest need to run?
Going by SKILL.md and its folder, Review Intelligence Digest needs the command-line tools its instructions call (python3) and credentials named APIFY_API_TOKEN. Our summary lists: Python 3; A credential in APIFY_API_TOKEN.
Does Review Intelligence Digest 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 Intelligence Digest 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 Intelligence Digest use?
Review Intelligence Digest 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 Intelligence Digest use?
About 1.7k tokens (SKILL.md is roughly 6.9k 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 Intelligence Digest?
Skills that share tags, products or a category with Review Intelligence Digest: Offers (Nexus-JPF/note-companion, 870 stars), Google Maps Reviews Scraper (gmapsscraper/google-maps-agent-skills, 132 stars), Amazon Reviews Extractor (browser-act/skills, 6.1k stars) and Outreach Manager (aaron-he-zhu/aaron-marketing-skills, 2.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Review Intelligence Digest?
gooseworks-ai (a GitHub organization) maintains it in gooseworks-ai/goose-skills, which has 1,240 GitHub stars. The repository holds 273 skills in this directory. The repository was last updated on October 8, 2026.
Source: gooseworks-ai/goose-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.