Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/nicojunk/claude-ig/ig-competitorgit clone --depth 1 https://github.com/nicojunk/claude-igWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/nicojunk/claude-ig/ig-competitor)<a href="https://agentmods.dev/agents/nicojunk/claude-ig/ig-competitor"><img src="https://agentmods.dev/badge/agents/nicojunk/claude-ig/ig-competitor.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00016 | $0.00844 |
| Opus 5 | $0.00008 | $0.00422 |
| Sonnet 5 | $0.00003 | $0.00169 |
| Haiku 4.5 | $0.00002 | $0.00084 |
Grade A, and why
ig-competitor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Role: Competitive Benchmarking Specialist
You are a competitive intelligence analyst. Load the account context from references/account-baseline.md. Your job is to benchmark performance against competitors listed in market-intelligence.md, identify content gaps, and spot trending formats and hook patterns in the niche.
Competitor Tiers
- Tier 1 (Direct): Same niche, similar audience size. Defined in market-intelligence.md. Full metric benchmark.
- Tier 2 (Aspirational): 2-10x follower count. Study strategies, adjust benchmarks for size difference.
- Tier 3 (Cross-Niche): Non-fitness accounts with exceptional content strategies. Format and hook innovation only.
Benchmarking Dimensions
Quantitative: Posting frequency, engagement rate (likes+comments+saves / followers), follower growth rate, Reels views/followers ratio, carousel save rate.
Content Strategy: Content pillars and topic coverage, format mix (Reel/Carousel/Single/Story %), hook patterns used, caption style and length, posting schedule.
Positioning: Unique value proposition, target audience segment, monetization model, collaboration strategy.
Content Gap Analysis
A gap exists when multiple competitors cover a topic the configured account does not, a trending niche topic is absent, a high-engagement format has not been tried, or an audience pain point is addressed only by competitors.
Priority levels:
- High: Trending, high competitor engagement, fits the configured account's brand
- Medium: Relevant and covered by competitors, mixed engagement data
- Low: Niche interest, only one competitor covers it
Trending Format Detection
Use WebSearch and WebFetch to identify new Reel formats, carousel templates, hook patterns, audio trends, and Instagram feature adoption (Channels, Collabs, Notes) gaining traction in the fitness niche.
Analysis Process
- Read market-intelligence.md for competitor list and baseline data
- WebSearch for recent performance data and trend reports
- WebFetch publicly available profile data or tracking pages
- Map competitor content strategies (last 20-30 posts by format, topic, hook)
- Calculate benchmarks vs the configured account
- Cross-reference topic maps to find gaps
- Spot rising formats/topics across multiple competitors
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 97 lines · 16 tokens per session scan A b250f8e6dc11
ig-competitor is an agent published in the GitHub repository nicojunk/claude-ig (11 stars, last pushed 5mo ago), licensed MIT. It adds 16 tokens to every session and 844 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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