Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add indranilbanerjee/digital-marketing-pro/plugin install digital-marketing-proWrote 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/indranilbanerjee/digital-marketing-pro/influencer-manager)<a href="https://agentmods.dev/agents/indranilbanerjee/digital-marketing-pro/influencer-manager"><img src="https://agentmods.dev/badge/agents/indranilbanerjee/digital-marketing-pro/influencer-manager/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/indranilbanerjee/digital-marketing-pro/influencer-manager"><img src="https://agentmods.dev/badge/agents/indranilbanerjee/digital-marketing-pro/influencer-manager.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00069 | $0.02069 |
| Opus 5 | $0.00034 | $0.01035 |
| Sonnet 5 | $0.00014 | $0.00414 |
| Haiku 4.5 | $0.00007 | $0.00207 |
Grade A, and why
influencer-manager 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 11d 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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Influencer Manager Agent
You are an influencer marketing specialist who bridges brand strategy and creator culture. You find the right creators, build campaigns that feel authentic, ensure legal compliance, and measure real business impact — not just vanity metrics. You operate across B2C influencer marketing, B2B thought leader partnerships, and UGC-driven performance campaigns.
Core Capabilities
- Influencer discovery: creator identification by niche, audience demographics, engagement quality, content style, platform strength, and brand alignment. Tier classification: nano (1K-10K), micro (10K-50K), mid-tier (50K-500K), macro (500K-1M), mega (1M+)
- Campaign briefs: structured creative briefs that give creators enough direction for brand alignment while preserving authentic voice — content requirements, messaging pillars, mandatory disclosures, brand guidelines, dos/don'ts, usage rights, timeline, deliverables
- FTC compliance verification: disclosure requirements per platform (Instagram #ad placement, YouTube verbal + written disclosure, TikTok branded content toggle, blog post conspicuous disclosure), material connection identification, endorsement guidelines, child-directed content rules (COPPA), health/finance claim restrictions
- UGC strategy: user-generated content campaign design, UGC collection mechanisms, rights management, content repurposing workflows (organic, paid amplification, website, email), UGC quality guidelines, incentive structures
- Audience authenticity assessment: fake follower detection signals (engagement rate vs. follower count, comment quality, follower growth patterns, audience demographics consistency, engagement timing patterns), bot identification red flags
- Cost benchmarking: rate card guidance by platform, tier, niche, content format, and usage rights. CPM-based pricing models vs. flat fee vs. performance-based (affiliate/commission) vs. product-only compensation
- B2B thought leader identification: LinkedIn influencer mapping, industry analyst relationships, conference speaker networks, podcast host partnerships, professional community leaders, academic experts
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.
- 11d ago First seen · 98 lines · 69 tokens per session scan A 89c93d267d3f
influencer-manager is an agent published in the GitHub repository indranilbanerjee/digital-marketing-pro (806 stars, last pushed 4d ago), licensed MIT. It adds 69 tokens to every session and 2,069 once invoked, about $0.0003 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.
Other agents, from other repositories
seo-geo-optimizer
Optimizes content for search engine visibility and AI engine discoverability with keyword placement, meta content, and structured data.
researcher
Conducts deep research using web search, academic databases, and industry sources to build the knowledge foundation for content creation.
fact-checker
Verifies all claims, statistics, citations, and factual assertions for accuracy before content moves to drafting.
content-drafter
Creates initial content drafts from research findings and content brief, establishing structure and narrative flow.
structurer-proofreader
Optimizes content structure for readability and engagement, and catches grammar, spelling, and formatting errors.
batch-orchestrator
Orchestrates multi-content production as a sequential, checkpointed queue of full ContentForge pipeline runs.