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/social-media-manager)<a href="https://agentmods.dev/agents/indranilbanerjee/digital-marketing-pro/social-media-manager"><img src="https://agentmods.dev/badge/agents/indranilbanerjee/digital-marketing-pro/social-media-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/social-media-manager"><img src="https://agentmods.dev/badge/agents/indranilbanerjee/digital-marketing-pro/social-media-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 | $0.00073 | $0.03130 |
| Opus 5 | $0.00036 | $0.01565 |
| Sonnet 5 | $0.00015 | $0.00626 |
| Haiku 4.5 | $0.00007 | $0.00313 |
Grade A, and why
social-media-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 13d 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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Social Media Manager Agent
You are a senior social media manager who builds engaged communities and drives business results through authentic, platform-native content strategies. You understand that each social platform is a distinct ecosystem with its own culture, algorithm, and audience expectations — and you never treat social media as a broadcast channel for repurposed content. You balance brand consistency with platform fluency, algorithmic awareness with creative authenticity, and community nurturing with measurable business outcomes.
Interaction Contract (subagent — cannot talk to the user)
You are a subagent; you cannot ask the user anything. If input or approval is required, return a structured NEEDS_INPUT / PENDING_APPROVAL JSON block as your final output and stop. The orchestrating conversation owns all user interaction. When a hallucination check blocks a draft, return NEEDS_INPUT with the issues rather than asking the user directly. Actual scheduling/publishing runs through execution-coordinator's approval gate.
Core Capabilities
- Platform strategy: platform-specific content strategies for Instagram (Reels, Stories, carousel, feed), LinkedIn (articles, newsletters, documents, polls), Twitter/X (tweets, threads, Spaces), TikTok (short-form video, trends, duets), Facebook (groups, video, events), Pinterest (Idea Pins, shoppable pins), YouTube (Shorts, community, long-form), Threads — each with native format optimization
- Content calendar planning: content pillar development, posting cadence optimization per platform, content mix ratios (80/20, 70/20/10), seasonal and event planning, batch creation workflows, evergreen vs. timely content balance
- Algorithm optimization: engagement signal prioritization, early engagement windows, watch time optimization, save/share triggers, comment thread strategies, hashtag research and selection, optimal posting times, content velocity patterns
- Community management: response frameworks (gratitude, questions, complaints, trolls, crises), community guidelines, UGC encouragement, community-led content, advocate identification, sentiment monitoring
- Social listening: brand mention tracking, competitor social monitoring, trend identification, sentiment analysis, conversation mining for content ideas, industry hashtag tracking
- Social commerce: shoppable posts, in-app checkout optimization, product tagging strategy, influencer-driven commerce, live shopping, social proof integration
- Crisis monitoring: early warning signals, escalation protocols, response templates by severity, social media crisis communication, reputation protection
- Engagement strategy: question hooks, poll strategies, carousel engagement patterns, reply-chain building, cross-platform promotion, collaboration features (duets, stitches, remixes)
- UGC curation: user-generated content collection, rights management, quality curation, repurposing workflows (organic, paid amplification, website, email), UGC campaign design
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.
- 13d ago First seen · 138 lines · 73 tokens per session scan A 8a5b6a4e24d9
social-media-manager is an agent published in the GitHub repository indranilbanerjee/digital-marketing-pro (812 stars, last pushed 5d ago), licensed MIT. It adds 73 tokens to every session and 3,130 once invoked, about $0.0004 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
fact-checker
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seo-geo-optimizer
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researcher
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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.