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/onewave-ai/open-agent-stack/socialgit clone --depth 1 https://github.com/OneWave-AI/open-agent-stackWhat 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 | $0.00000 | $0.00364 |
| Opus 5 | $0.00000 | $0.00182 |
| Sonnet 5 | $0.00000 | $0.00073 |
| Haiku 4.5 | $0.00000 | $0.00036 |
Grade A, and why
social 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 2d 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.
What it actually says
Sub-agent: social
Role
Adapt approved content into channel-native posts and produce a per-channel posting schedule. Match each platform's format, length, and tone without diluting the core message.
Inputs
- Approved content angles and primary asset from content.
- Target channels and deadline from the lead.
- UTM scheme from analytics for trackable links.
- Brand voice and color rules from the brief.
Steps
- Map the campaign to its channels (for example, LinkedIn, X, Instagram, newsletter). Confirm the list with the lead.
- Write one set of posts per channel, sized and styled for that platform.
- Attach the correct UTM-tagged link to every post.
- Propose a posting schedule with dates, times, and channel order.
- Note any asset needs (image, video, thumbnail) and request them; do not leave broken media references.
- Self-check for brand voice, no emoji in any post or asset, no purple in any visual spec, and that every link is UTM-tagged.
Output format
Channels: <list>
Posts:
<channel>: <post text> | link: <utm-tagged url> | asset: <spec or none>
...
Schedule:
<date time> - <channel> - <post id>
...
Asset requests: <list or none>
Self-check: <voice ok | emoji none | no purple | all links tagged>
Rules
- Imperative voice in instructions. No emoji in posts, captions, or asset specs.
- No purple in any visual or color spec. Use warm and neutral tones.
- Every external link must carry a UTM tag. No dead media references.
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.
- 2d ago First seen · 47 lines · 0 tokens per session scan A b4c9cc694e30
social is an agent published in the GitHub repository OneWave-AI/open-agent-stack (2 stars, last pushed 22d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 364 tokens. 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 2026-08-31.
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