Agno is a framework and runtime for building, running, and managing platforms made of AI agents. Developers use its SDK, service runtime, and web interface to create agent applications with storage, integrations, APIs, and operational controls; the catalogue entries provide agent-oriented workflows and configuration for using Agno.
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 skills add agno-agi/agno --skill refreshgit clone --depth 1 https://github.com/agno-agi/agnoWrote 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/skills/agno-agi/agno/refresh)<a href="https://agentmods.dev/skills/agno-agi/agno/refresh"><img src="https://agentmods.dev/badge/skills/agno-agi/agno/refresh/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/skills/agno-agi/agno/refresh"><img src="https://agentmods.dev/badge/skills/agno-agi/agno/refresh.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 | $0.00012 | $0.00302 |
| Opus 5.5 | $0.00005 | $0.00121 |
| Sonnet 5.5 | $0.00002 | $0.00060 |
| Haiku 4.5 | $0.00001 | $0.00030 |
Grade A, and why
refresh 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
Read the Product identified in the message. Read its playbook, then call refresh_company_product for that Product. This applies its archive window (metadata.archive_window_days, default 14) and returns Project completion proposals saved in the wiki. It never completes a Project. Present those proposals for a human to accept through the Project transition API; never transition directly. Read the remaining Projects and Tasks, then inspect configured Sources with read_company_source. Reflect observed progress and failures in status.md using its current version. On a conflict, read again and incorporate intervening changes. Propose changes for human review; never accept work or mark a Task Ready or Done. Remove references to archived work from status.md so it no longer enters executor context. Keep brief.md and status.md; maintenance only deletes recognized generated pages older than the window. If nothing changed, return a quiet successful check without writing duplicate pages. Report a maintenance failure instead of claiming success.
For each Source, call read_company_source without path for a paged, content-free index. Use pattern and next_offset to narrow discovery. Pass a returned path to read one document; next_content_offset continues large documents. Compare the full-document content_hash across fragments and reread if it changes. Never infer content from an index entry. Use intake_company_source for Task proposals; propose_company_task is unavailable to Routines.
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 · 26 lines · 12 tokens per session scan A d68cdacf341b
refresh is a skill published in the GitHub repository agno-agi/agno (42,799 stars, last pushed yesterday), licensed Apache-2.0. It adds 12 tokens to every session and 302 once invoked, about $0.0000 per session on Opus 5.5. 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 2026-10-17.
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