Apify Competitor Intelligence

What it does

When your agent uses it

• Tasks that involve Web scraping

Example prompts

• “/apify-competitor-intelligence”

Requirements

• Node.js
• A credential in APIFY_TOKEN

Workflow steps

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

1. 1Identify Competitor Analysis Type
2. 2Fetch Actor Schema
3. 3Ask User Preferences
4. 4Run the Script
5. 5Summarize Findings

What it can do on your machine

Read from SKILL.md and the folder at commit 331ecd3. 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

  Ships script files (JavaScript), which the agent can run.

  Shell commands in SKILL.md call:

  • node
  • npm
  • jq

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md. Its commands use npm, which can reach the network depending on how they are called.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names these keys or tokens, usually read from environment variables:

  • APIFY_TOKEN

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Apify Competitor Intelligence loads about 1.3k tokens when it runs. Until then it costs about 45 tokens; SKILL.md has 402 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~45

When it runs · the whole SKILL.md, loaded when a task matches

~1.3k

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

• NoteMentions a .env fileSKILL.md:13

  - `.env` file with `APIFY_TOKEN`

• NoteMentions a .env fileSKILL.md:70

  export $(grep APIFY_TOKEN .env | xargs) && mcpc --json mcp.apify.com --header "Authorization: Bearer $APIFY_TOKEN" tools

• NoteMentions a .env fileSKILL.md:93

  node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \

• NoteMentions a .env fileSKILL.md:100

  node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \

• NoteMentions a .env fileSKILL.md:109

  node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \

• NoteMentions a .env fileSKILL.md:127

  Y_TOKEN not found` - Ask user to create `.env` with `APIFY_TOKEN=your_token`

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 aAAaqwq/AGI-Super-Team at commit 331ecd3, republished under its MIT licence (© aAAaqwq). 402 words, ~1,322 tokens.

name

apify-competitor-intelligence

description

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

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

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"

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

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

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

© aAAaqwq, 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/apify-competitor-intelligence of aAAaqwq/AGI-Super-Team.

• SKILL.md
• reference/scripts/run_actor.js

Open the folder on GitHubat commit 331ecd3

Used in 3 other repositories

We found 12 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in aAAaqwq/AGI-Super-Team, which our catalogue first saw on October 9, 2026.

• sickn33/agentic-awesome-skillsskills/apify-competitor-intelligenceplugins/agentic-awesome-skills/skills/apify-competitor-intelligence+1 more
• lingxling/awesome-skills-cnantigravity-awesome-skills/skills/apify-competitor-intelligenceantigravity-awesome-skills/plugins/agentic-awesome-skills/skills/apify-competitor-intelligence+1 more
• henryalouf/ruflow.agents/skills/apify-competitor-intelligence.agents/skills/antigravity-awesome-skills/skills/apify-competitor-intelligence+4 more