Ante is a self-contained coding agent that runs in a terminal and can be configured with a user-defined profile and system prompt. It is intended for coding assistance across different models and can also serve as a core for custom agent harnesses. The catalogue includes one skill for use with Ante.
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 AntigmaLabs/ante --skill simplifygit clone --depth 1 https://github.com/AntigmaLabs/anteWrote 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/antigmalabs/ante/simplify)<a href="https://agentmods.dev/skills/antigmalabs/ante/simplify"><img src="https://agentmods.dev/badge/skills/antigmalabs/ante/simplify.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 | $0.00043 | $0.00475 |
| Opus 5 | $0.00022 | $0.00237 |
| Sonnet 5 | $0.00009 | $0.00095 |
| Haiku 4.5 | $0.00004 | $0.00047 |
Grade A, and why
simplify 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 today.
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 — 41 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Simplify
Improve the quality of changed code while preserving intended behavior. Focus on cleanup; correctness bug hunting is outside this skill’s scope.
Assume a Git codebase and an available subagent tool.
Establish scope
Honor the user’s explicit target; otherwise review changes relevant to the current task. Choose comparison revisions from repository and conversation context. Include staged, unstaged, and relevant untracked changes.
Use this scope consistently across reviewers. Read surrounding code as needed to understand behavior and find existing implementations.
Review with subagents
Assign each lens below to an independent subagent. Run reviews in parallel within available capacity.
Give every reviewer the same scope, access to the diff, and relevant task context. Reviewers return findings without editing files.
- Reuse: Identify new code that duplicates existing functionality. Search shared utilities and adjacent code, and name the existing implementation to use.
- Simplification: Identify redundant or derivable state, repeated logic, unnecessary nesting or indirection, and dead code introduced or left behind by the changes. Name the simpler equivalent.
- Efficiency: Identify wasted computation, repeated I/O, unnecessary retention, or avoidable blocking. Explain the cost in its actual execution context and name a cheaper alternative.
- Abstraction: Check whether the change belongs at the right layer. Identify special cases that would become unnecessary by improving the underlying mechanism. Propose a deeper change only when it reduces overall complexity.
Each finding should include file, line, a short summary, the concrete cost, and a proposed improvement. Return no findings when no worthwhile improvement is supported.
Apply and verify
Wait for all reviews. Deduplicate findings that concern the same code or underlying mechanism, then validate the remaining findings against the surrounding code and intended behavior.
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.
- today First seen · 41 lines · 43 tokens per session scan A b81bb807fda7
simplify is a skill published in the GitHub repository AntigmaLabs/ante (1,942 stars, last pushed today), licensed Apache-2.0. It adds 43 tokens to every session and 475 once invoked, about $0.0002 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 2026-09-08.
Other skills, from other repositories
review
Review code changes, pull requests, patches, or a scoped code area for actionable correctness, security, compatibility, and test risks with file and line evidence. Use for review or audit requests; do not use for general proofreading, feature implementation, or debugging a reported failure when the user wants a fix.
simplify
Reduce unnecessary code complexity, duplication, indirection, or abstraction while preserving observable behavior and validating equivalence. Use for simplify, cleanup, or behavior-preserving refactor requests; do not use for adding features, diagnosing an unexplained failure, broad code review without a…
debug
Diagnose a concrete failure, regression, crash, hang, flaky test, or incorrect runtime behavior by reproducing it, testing hypotheses, and identifying the evidence-backed root cause. Use when symptoms or failing output exist; do not use for feature implementation without a failure, general code review, or a conceptual…
simplify-code
Sequential 3-lens cleanup of recent code changes.
GitHub Code Review
Review pull requests with a bug-first mindset, grounding findings in concrete diff context and repository behavior.
hqe
Comprehensive codebase health auditing, remediation, and verification skill based on the canonical HQE Protocol v5.0.0.