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AA analyzing-competitor-instagram-content-strategy

Analyzes a competitor's Instagram content strategy and performance using apidojo's Instagram scraper on Apify. Triggers when the user asks to: analyze what a competitor posts on Instagram, benchmark a competitor's Instagram engagement, see what content types perform best for a competitor on Instagram, reverse-engineer a competitor's Instagram content calendar, identify content gaps vs. a competitor on Instagram, compare posting frequency or content themes, or understand why a competitor's Instagram is growing. Returns post frequency, content type mix, top-performing posts, hashtag strategy, and engagement benchmarks. Ideal for social media managers, brand strategists, and content marketing teams.

ClawHub Agent Skills author: API Dojo v0.1.0 MIT-0 2 files body ≈ 1 308 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

Analyzes a competitor's Instagram content strategy and performance using apidojo's Instagram scraper on Apify.

As a process A 81/100 · Runs to the end — weak spots: progress reporting

AnalyzerMarketingtype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
98
Quality 40%
88
Run on models
none yet
Process rating
A
81/100
Runs to the end
Progress reporting w 2
0
Failures and branches w 10
50
Result and completion w 14
60
the three weakest of ten parameters · all ten

How to improve

    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

    ✓ No critical or high findings

    Medium and low: 2
    • low Exfiltration exfil-secret-in-url SKILL.md:86
      Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
      curl -X POST   "https://api.apify.com/v2/acts/apidojo~instagram-scraper/runs?token=…"   -H "Content-Type: application/json"   -d '{"usernames": ["competitor_handle"], "maxItems": 50}'
      placeholder
    • low Exfiltration net-credential-use SKILL.md:86
      Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
      curl -X POST   "https://api.apify.com/v2/acts/apidojo~instagram-scraper/runs?token=…"   -H "Content-Type: application/json"   -d '{"usernames": ["competitor_handle"], "maxItems": 50}'
      vendor-host

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 81/100

    • 0Progress reporting. Says nothing while it works
    • 50Failures and branches. 0 branches, has a failure section
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 6 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1308 tokens
    • 100Running it twice. No mutating operations

    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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +2Single-language instructions
    • +3Description length 705: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 6 items
    • +3Output format is stated explicitly
    • +4Has examples (8 code blocks)
    • +1License stated

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

    External checks

    ClawHub: clean
    This skill is a straightforward Instagram competitor-analysis workflow that uses Apify as disclosed, with no hidden persistence or unrelated data handling found.
    LLM: benign (high) · VirusTotal: · 3 Sept 2026