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CB apify-easy-competitive-intelligence

This skill should be used when the user asks to "analyze a competitor", "compare pricing", "competitive landscape", "market research", "what do customers think", "review intelligence", "hiring signals", "content strategy", "SEO battle", "build a battlecard", "competitive analysis", "who are the players", "who competes with", "market intelligence", "competitive positioning", "deep dive on a company", "board prep", "SWOT analysis", "how does [X] compare to [Y]", or mentions competitor analysis, pricing comparison, customer sentiment, or market landscape research. Requires Apify CLI or Apify MCP server.

Not recommendedcritical or high security findings
apify/awesome-skills Agent Skills author: apify 11 files body ≈ 2 267 tokens Open the sourcegithub.com↗ analyzed 3 d ago

This skill should be used when the user asks to "analyze a competitor", "compare pricing", "competitive landscape", "market research", "what do customers…

As a process B 71/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting

AnalyzerMarketingAI and agentsPeople and hiringtype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
84/100
safety, quality, tests
Safety 60%
81
Quality 40%
88
Run on models
none yet
Process rating
B
71/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Exfiltration
If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 2

  • high Exfiltration intent-browser-credential-store SKILL.md:21
    Accesses a browser credential / cookie store
    Real-time competitive intelligence powered by live web data via Apify actors. **Never answer competitive questions from training knowledge alone.** Always gather live data first, then analyze.
Medium and low: 1
  • low Exfiltration read-dotenv SKILL.md:46
    Reads a .env file (detector / deny-list definition)
    3. **From .env file:** `source .env` (if the file contains `APIFY_TOKEN=...`)
    detector

Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • note frontmatter-key unknown frontmatter key "author_url"

Process rating: all ten parameters 71/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 1 mutating operations with no state check
  • 60Tools and files. Uses tools (web, python, node) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 39 steps
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2267 tokens

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 19 example trigger phrases
  • +3Description length 607: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 39 items
  • +4Reference files are cited in the instructions (3 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.