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Competitor Intelligence · sickn33 | DecimalAI

Apify Competitor Intelligence

SkillScore65Maintained

apify-competitor-intelligence

Analyze competitor strategies, content, pricing, ads, and market positioning across Google Maps, Booking.com, Facebook, Instagram, YouTube, and TikTok.

researchby sickn33

Links this skill to your agents and keeps it current with the author’s updates.

Automatic

Sales & GTM pack

1 · One-time — install the CLI (docs ↗)

pip install decimalai

2 · Get the skill — writes .claude/skills/apify-competitor-intelligence/SKILL.md

decimalai skills pull apify-competitor-intelligence --out .claude/skills/

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/apify-competitor-intelligence/SKILL.md https://app.decimal.ai/s/apify-competitor-intelligence/SKILL.md

Raw file: /s/apify-competitor-intelligence/SKILL.md ↗ · machine-readable summary at /s/apify-competitor-intelligence.json ↗

In productionGlobal

how this skill behaves on real traffic · last 30 days

No production data for this skill yet — usage numbers appear here once agents start running it.

Anonymized aggregate across every org using this skill — proof from real production use, not a demo.

Does this skill help? · Benchmark: with vs. withoutsign in to run this on your agents

23 test cases from the publisher’s eval.yaml · each run twice on gemini-3.6-flash — with the skill injected, then without · last run 61d ago

Yes — +61% lift · at higher cost+30% tokens0% turns65% of whole cases pass with skill (15/23)

Test case	Without → With	Effect	Δ tokens	Δ turns
case-18	✗→✓	▲ Improved	—	—
case-19	✗→✓	▲ Improved	—	—
case-23	✗→✓	▲ Improved	—	—
case-06	✗→✓	▲ Improved	—	—
case-14	✗→✓	▲ Improved	—	—

Showing 5 of 23 cases

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 7/30/2026

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

sickn33 / antigravity-awesome-skills

skills/apify-competitor-intelligence/SKILL.md

View on GitHub ↗

License MITImported 9/11/2026Version v1

Skill contents

SKILL.md

Competitor Intelligence

Analyze competitors using Apify Actors to extract data from multiple platforms.

When to Use

You need competitor benchmarks for content, reviews, pricing, ads, audience, or channel performance.
The task involves selecting Apify Actors to compare competitors across maps, booking, social, or video platforms.
You need structured competitor data plus synthesized takeaways for strategy or positioning.

Prerequisites

(No need to check it upfront)

.env file with APIFY_TOKEN
Node.js 20.6+ (for native --env-file support)
mcpc CLI tool: npm install -g @apify/mcpc

Workflow

Copy this checklist and track progress:

Task Progress:
- [ ] Step 1: Identify competitor analysis type (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the analysis script
- [ ] Step 5: Summarize findings

Step 1: Identify Competitor Analysis Type

Select the appropriate Actor based on analysis needs:

| User Need | Actor ID | Best For | |-----------|----------|----------| | Competitor business data | compass/crawler-google-places | Location analysis | | Competitor contact discovery | poidata/google-maps-email-extractor | Email extraction | | Feature benchmarking | compass/google-maps-extractor | Detailed business data | | Competitor review analysis | compass/Google-Maps-Reviews-Scraper | Review comparison | | Hotel competitor data | voyager/booking-scraper | Hotel benchmarking | | Hotel review comparison | voyager/booking-reviews-scraper | Review analysis | | Competitor ad strategies | apify/facebook-ads-scraper | Ad creative analysis | | Competitor page metrics | apify/facebook-pages-scraper | Page performance | | Competitor content analysis | apify/facebook-posts-scraper | Post strategies | | Competitor reels performance | apify/facebook-reels-scraper | Reels analysis | | Competitor audience analysis | apify/facebook-comments-scraper | Comment sentiment | | Competitor event monitoring | apify/facebook-events-scraper | Event tracking | | Competitor audience overlap | apify/facebook-followers-following-scraper | Follower analysis | | Competitor review benchmarking | apify/facebook-reviews-scraper | Review comparison | | Competitor ad monitoring | apify/facebook-search-scraper | Ad discovery | | Competitor profile metrics | apify/instagram-profile-scraper | Profile analysis | | Competitor content monitoring | apify/instagram-post-scraper | Post tracking | | Competitor engagement analysis | apify/instagram-comment-scraper | Comment analysis | | Competitor reel performance | apify/instagram-reel-scraper | Reel metrics | | Competitor growth tracking | apify/instagram-followers-count-scraper | Follower tracking | | Comprehensive competitor data | apify/instagram-scraper | Full analysis | | API-based competitor analysis | apify/instagram-api-scraper | API access | | Competitor video analysis | streamers/youtube-scraper | Video metrics | | Competitor sentiment analysis | streamers/youtube-comments-scraper | Comment sentiment | | Competitor channel metrics | streamers/youtube-channel-scraper | Channel analysis | | TikTok competitor analysis | clockworks/tiktok-scraper | TikTok data | | Competitor video strategies | clockworks/tiktok-video-scraper | Video analysis | | Competitor TikTok profiles | clockworks/tiktok-profile-scraper | Profile data |

Step 2: Fetch Actor Schema

Fetch the Actor's input schema and details dynamically using mcpc:

bash
export $(grep APIFY_TOKEN .env | xargs) && mcpc --json mcp.apify.com --header "Authorization: Bearer $APIFY_TOKEN" tools-call fetch-actor-details actor:="ACTOR_ID" | jq -r ".content"

Replace ACTOR_ID with the selected Actor (e.g., compass/crawler-google-places).

This returns:

Actor description and README
Required and optional input parameters
Output fields (if available)

Step 3: Ask User Preferences

Before running, ask:

Output format:

Quick answer - Display top few results in chat (no file saved)
CSV - Full export with all fields
JSON - Full export in JSON format

Number of results: Based on character of use case

Step 4: Run the Script

Quick answer (display in chat, no file):

bash
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT'

CSV:

bash
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT' \
  --output YYYY-MM-DD_OUTPUT_FILE.csv \
  --format csv

JSON:

bash
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT' \
  --output YYYY-MM-DD_OUTPUT_FILE.json \
  --format json

Step 5: Summarize Findings

After completion, report:

Number of competitors analyzed
File location and name
Key competitive insights
Suggested next steps (deeper analysis, benchmarking)

Error Handling

APIFY_TOKEN not found - Ask user to create .env with APIFY_TOKEN=your_token mcpc not found - Ask user to install npm install -g @apify/mcpc Actor not found - Check Actor ID spelling Run FAILED - Ask user to check Apify console link in error output Timeout - Reduce input size or increase --timeout

Limitations

Use this skill only when the task clearly matches the scope described above.
Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Illustrative Want to see what apify-competitor-intelligence would put in front of your model? Preview the rendered body and check its trigger phrases — no LLM call, no signup.

Latest benchmark · publisher runVerified

7/28/2026, 15:44 UTC · 23 cases

Lift

+61%

65% vs 4%

Agent turns

1.0 vs 1.0

Tokens

+30%

2,256.04 vs 1,739.43

fail → pass · 14pass → pass · 1fail → fail · 8

Per-case results (23)

Case	Status	Duration (ms)			Turns			Tokens			Tool calls
Case	Status	Without	With	Δ	Without	With	Δ	Without	With	Δ	Without	With	Δ
case-11 We need to fetch guest reviews and ratings specifically for rival hotels on Booking.com to analyze recurring customer complaints. Which actor ID handles Booking review data?	pass→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-18 We need to execute a competitive search analysis on Facebook and write the output directly to a JSON file named 2025-06-01_fb_search.json. What exact script parameter specifies the output format?	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-21 We need to parse our internal company sales JSON feeds and clean up product catalog data. Should pre-built social media and public web scraping actors be used for this internal data transformation task?	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-19 We want to analyze customer sentiment and discussion topics inside comment sections on competitor YouTube video uploads. Which actor ID is designated for YouTube comment collection?	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-23 I need to set up a paid Google Ads campaign for our SaaS product, including keyword bidding strategy, ad copy extensions, and daily budget capping in Google Ads Manager.	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-06 We need to analyze view counts, upload frequency, and engagement metrics across five competitor YouTube channels. Outline the tool selection and schema verification step.	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-14 I need to run an Instagram reel performance benchmark and output the full result set to a CSV file named 2025-05-10_reels_benchmarks.csv. What command options are passed to the execution script?	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-09 We want to pull bio information, overall follower counts, and account-level metrics for ten competitor TikTok profiles. Which actor ID is best suited for profile-level data?	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-12 How should the input schema and parameter requirements be dynamically fetched for the actor compass/crawler-google-places using CLI tooling?	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-15 When running a competitive scrape script, the log returns APIFY_TOKEN not found. What troubleshooting guidance should be provided to the user?	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-08 Our brand wants to compare high-level page metrics across four Facebook business pages of competitors. Which actor ID handles this page-level analysis?	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-07 We need to gather contact email addresses for local competitor storefronts based on their Google Maps listings. Which actor handles this specific extraction task?	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-05 Our marketing team wants to analyze room pricing and availability across rival hotels listed on Booking.com. What exact data actor should be queried, and what command structure runs it with environment variables loaded?	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-22 We want to conduct organic search keyword research and backlink domain authority analysis using third-party SEO platforms. Can you set up the scraper run and export domain metrics?	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-13 I want a quick snippet of top competitor search results from Facebook displayed directly in chat without creating any output files on disk. What command is used for this file-less execution?	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-10 We need to monitor post text, posting cadence, and post-level performance across our competitors' official Facebook pages. Which actor ID addresses post content analysis?	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-16 While attempting to fetch actor schema, the terminal displays mcpc: command not found. How should this setup error be resolved?	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-04 We want to track our competitors' active Facebook ad creative campaigns to see what messaging and imagery they are testing. Walk through how you will fetch the tool schema, ask for my preferred report format, and trigger the run.	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-02 We are looking to compare customer reviews across several local competitor locations using Google Maps data. Please set up the extraction process, query me regarding output preferences like file format or display option, run the data pull, and present a summary of competitor sentiment along with suggested next steps.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-20 Our video team wants to compare short-form reel reach and interaction metrics on competitors' Facebook pages. Which actor ID specifically targets Facebook reel data?	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-17 An actor execution task targeting a large dataset timed out before completion. What actionable options troubleshoot this timeout?	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-01 I need to perform a competitive analysis on our top three rivals' Instagram accounts to benchmark their follower counts, post metrics, and overall engagement. Could you handle setting up the appropriate data collection tool, ask for my preferences on format and result volume, execute the retrieval, and summarize the key strategic takeaways?	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-03 I need an audit of our competitors' TikTok video strategies to see which creative formats are getting the most engagement. Please select the right workflow, ask me how I want the output delivered and how many items to collect, run the analysis, and deliver a high-level summary of competitive findings.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—

These cases were also screened by the skill’s intent / safety pass.See the Trust review ↗Reproduce this benchmark in Colab ↗

How this skill was measured

DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted. The headline lift of +61 percentage points is the difference between those two pass rates over the 23 comparable cases.

Model measured: gemini-3.6-flash
Graded by: gemini-3.6-flash
Grading method: judged
Verification: verified
Pass rate without the skill: 4.4%
Pass rate with the skill: 65.2%
Cases attempted: 23
Cases counted toward lift: 23
Cases that regressed: 0
Skill version measured: v1
Run completed: 7/28/2026, 15:44 UTC

The per-case answers from this run were removed by the retention sweep, so the case table below shows the verdicts without the text either arm produced. The counts above were recorded at the time and are unaffected. Answers are now kept for 180 days.

SkillScore blends 4 signals1 of 4 complete

BenchmarkPass rate WITH skill on a verified run65

Live evalNeeds ≥10 evaluated traces in 30 days

AI ratingNeeds ≥10 rated traces

AdoptionNeeds ≥10 serves across ≥2 orgs in 30 days

Efficiency · separate axis (at equal correctness)+0% turns+34% tokens

Shown for transparency; not credited unless a verified run shows no correctness regression.

Backed by 1 of 4 signals — each added signal makes the score more robust.

Verified on gemini-3.6-flash · re-tested 2 months ago

Other measured skills in the registry, with their headline benchmark lift.