Mini Agent is a small demonstration application for building a single AI agent with the MiniMax M2.5 model, an Anthropic-compatible API, tools, memory, and context handling. It is intended as a starting point for developing and debugging agents, and includes skills and MCP integrations that extend the agent's workflow.
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 skills/minimax-ai/mini-agent/template-skillnpx skills add MiniMax-AI/Mini-Agent --skill template-skillgit clone --depth 1 https://github.com/MiniMax-AI/Mini-AgentWrote 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/minimax-ai/mini-agent/template-skill)<a href="https://agentmods.dev/skills/minimax-ai/mini-agent/template-skill"><img src="https://agentmods.dev/badge/skills/minimax-ai/mini-agent/template-skill.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 5.1 | $0.00017 | $0.00028 |
| Opus 5 | $0.00009 | $0.00014 |
| Sonnet 5 | $0.00003 | $0.00006 |
| Haiku 4.5 | $0.00002 | $0.00003 |
Grade A, and why
template-skill 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 6d 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- template-skill — 100% identical, 0 lines differ
- template-skill — 100% identical, 0 lines differ
- template-skill — 100% identical, 0 lines differ
- template-skill — 100% identical, 0 lines differ
- template-skill — 100% identical, 0 lines differ
- template-skill — 100% identical, 1 lines differ
- template-skill — 100% identical, 0 lines differ
- template-skill — 100% identical, 0 lines differ
What it actually says
Insert instructions below
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.
- 6d ago First seen · 7 lines · 17 tokens per session scan A eb685d91de03
template-skill is a skill published in the GitHub repository MiniMax-AI/Mini-Agent (3,010 stars, last pushed 6mo ago), licensed MIT. It adds 17 tokens to every session and 28 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.
Other skills, from other repositories
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continual-learning
Nightly refinement of an existing per-repo review-style prompt using this reviewer's own finding outcomes. Read confirmed (resolved-by-commit / thumbs-up) and dismissed (thumbs-down) findings, promote the bug patterns the team actually fixes, demote the false-positive patterns, reconcile against the current prompt…
nano-banana-pro-openrouter
Deterministic OpenRouter image generation adapter for Nano Banana Pro / Gemini image models. Use as skillexec when a meta-skill needs local image files and structured IMAGEREADY records without spawning an LLM agent.
skill-creator-linter
Internal tool (not user-invocable). Called by meta-skill-creator as a DAG step (kind: agent) to lint a candidate meta-skill SKILL.md against G1 (parse + reference check + xmlescape grep + structural lint) and G2 (scheduler dry-run with stub executors). Deterministic, sub-second, no LLM. Returns JSON diagnostics.
paper-abstract-author
Write the abstract after the paper body has been revised, using the final claims and evidence.
clinicaltrials-database
Query ClinicalTrials.gov via API v2. Search trials by condition, drug, location, status, or phase. Retrieve trial details by NCT ID, export data, for clinical research and patient matching.