Anima is an open-source local-network runtime that gives household hardware an AI layer for sensing environments, remembering preferences, planning actions, and controlling devices through adapters. It is intended for intelligent devices such as lights, air conditioners, humidifiers, air purifiers, and speakers, with a dashboard, REST API, and CLI for control and extension. The catalogue entries are skills, rules, and instructions for working with Anima.
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.
git clone --depth 1 https://github.com/Fullive-AI/AnimaWrote 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/rules/fullive-ai/anima/verification-and-regression-checks)<a href="https://agentmods.dev/rules/fullive-ai/anima/verification-and-regression-checks"><img src="https://agentmods.dev/badge/rules/fullive-ai/anima/verification-and-regression-checks/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/rules/fullive-ai/anima/verification-and-regression-checks"><img src="https://agentmods.dev/badge/rules/fullive-ai/anima/verification-and-regression-checks.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 | $0.00309 | $0.00309 |
| Opus 5.5 | $0.00124 | $0.00124 |
| Sonnet 5.5 | $0.00062 | $0.00062 |
| Haiku 4.5 | $0.00031 | $0.00031 |
Grade A, and why
Verification-And-Regression-Checks 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 1mo 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
Every meaningful change should be validated as strongly as the repo allows.
Required behavior
After making changes, run the most relevant available checks, such as:
- targeted tests
- affected test suites
- lint
- type-check
- build
- static analysis
- framework-specific validation commands
Do not skip validation just because the code looks correct.
Validation strategy
Prefer this order:
- run the most targeted checks first
- fix failures
- run broader relevant checks as needed
- confirm the task outcome
- watch for regressions in adjacent behavior
Bug fix rule
For bug fixes:
- verify the original failure mode is addressed
- add or update a regression test when feasible
- confirm related behavior still works
Feature rule
For features:
- validate the happy path
- validate obvious edge states
- ensure the feature is actually wired into the real flow
- confirm types, imports, and integration points are correct
Failure handling
If a validation step fails:
- diagnose the failure
- determine whether it is caused by your change
- fix it if in scope or required for correctness
- re-run validation
- continue until passing or truly blocked
Minimum expectation
Never treat "edited code successfully" as equivalent to "task completed successfully."
Reporting
When summarizing work, include:
- what was validated
- what passed
- what could not be validated
- any remaining caveats
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.
- 1mo ago First seen · 70 lines · 309 tokens per session scan A c7523e5859fc
Verification-And-Regression-Checks is a cursor rule published in the GitHub repository Fullive-AI/Anima (636 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 309 tokens to every session, about $0.0012 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 2026-08-30.
Other cursor rules, from other repositories
fuzzing
Fuzzing setup and guidelines for skia-rs.
testing-and-quality
The testcomprehensive.py provides systematic testing of all 31 MCP tools.
smoke-monkey-tester
Smoke tests for core functionality and monkey/chaos tests aiming to break the system with randomized inputs. / TR: Sistemin temel fonksiyonlarını kontrol eden smoke testler ve rastgele girdilerle sistemi çökertmeyi hedefleyen monkey/chaos testleri.
testing
Testing conventions for Ion Design System using Jest and Angular Testing Library.
STAGE_S5_TEST_POINTS
A staged workflow for turning approved requirements into a complete list of test points. It checks required earlier documents and records any requirement that has no matching test point.
pre-flight-check
Mandatory fail-fast quality gate — run Typecheck, Lint, Test, and Security Audit sequentially before declaring any task done or committing code.