compass-calendar: Skill for Codex

.agents/skills/chaos/SKILL.md

chaos is a skill for Codex from KeepSoftwareSimple/compass-calendar. It costs 79 tokens per session (1,596 once invoked), scanned A, original, MIT.

A guide for exploratory testing of a signed-in web product, starting with the normal user flow and then checking focused failure cases. It covers investigating and fixing confirmed user-interface, security, reliability, performance, accessibility, and data problems.

In plain words
What is it for?
Use it before a release or for exploratory testing in a local or approved non-production environment, especially when checking authenticated flows and data changes.
Why use it?
It provides boundaries for testing real accounts without collecting credentials or touching production systems by default. It also emphasizes reproducible evidence and preserving existing data.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: installed under .agents/ (shared by several agents); mentions AGENTS.md.

This is KeepSoftwareSimple/compass-calendar's own configuration. It tells Codex how to work on compass-calendar itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything compass-calendar configures →

Reuse

Borrowing it

Nothing to install: this file belongs to KeepSoftwareSimple/compass-calendar. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/KeepSoftwareSimple/compass-calendar/main/.agents/skills/chaos/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/KeepSoftwareSimple/compass-calendar

Made for: Codex.

Wrote 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.

agentmods badge for chaos

README.md
[![agentmods](https://agentmods.dev/badge/skills/keepsoftwaresimple/compass-calendar/chaos/github.svg)](https://agentmods.dev/skills/keepsoftwaresimple/compass-calendar/chaos)
Your own site
<a href="https://agentmods.dev/skills/keepsoftwaresimple/compass-calendar/chaos"><img src="https://agentmods.dev/badge/skills/keepsoftwaresimple/compass-calendar/chaos/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.

agentmods 80×15 button for chaos

Your own site · 80×15
<a href="https://agentmods.dev/skills/keepsoftwaresimple/compass-calendar/chaos"><img src="https://agentmods.dev/badge/skills/keepsoftwaresimple/compass-calendar/chaos.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 79 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,596 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00079 $0.01596
Opus 5.5 $0.00032 $0.00638
Sonnet 5.5 $0.00016 $0.00319
Haiku 4.5 $0.00008 $0.00160

Measured yesterday against content hash b3caeb0e332f, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

chaos 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 yesterday.

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.

.agents/skills/chaos/SKILL.md · 158 lines

How it starts

The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.

When

Before a production release, or when asked for exploratory / chaos testing.

Steps

Prepare → happy path → focused probes → diagnose/fix → simplify/review/ship.

Output

Evidence of signed-in exercise plus shipped fixes, or a report of stops.

Pass

Happy path worked; probes were focused; credentials were not entered by the agent.

Anti-patterns

Do not enter credentials. See anti-patterns.md.

Escalate

Auth/setup missing, production-only defect, or a product fork.

Chaos

Treat a real, existing signed-in profile as an observation and interaction surface—not a source for credentials, cookies, tokens, or private data. Build confidence from visible behavior and reproducible evidence, then make the smallest fix that removes a confirmed defect.

Boundaries

  • Target local development or an explicitly named non-production environment. Never probe production, payment flows, or third-party systems by default.
  • Verify the selected account visibly before mutating data. If the expected test account is unknown, ambiguous, or not signed in, stop and ask the user.
  • Use unique, clearly test-labelled records. Preserve pre-existing records; remove only records created by this run through the normal recoverable UI, then reload to confirm cleanup persisted.
  • Do not enter credentials, grant/revoke OAuth, change account/security settings, bypass browser security warnings, or perform irreversible actions. Report those cases with a safe manual reproduction instead.
  • Bound adversarial testing: do not use load generation, fuzz external APIs, scrape data, bypass authorization, or test other users' data. Test only the current account and normal product surfaces.
  • Treat an exception, failed request, data loss, stale UI, inaccessible flow, privacy exposure, or significant interaction latency as a finding even when the UI appears to complete the action.

1. Prepare the test surface

  1. Read AGENTS.md, inspect the current branch and diff, and identify the release-critical and recently changed user-visible flows.
  2. Read the relevant acceptance docs and tests. Follow docs/development/local-development.md if the required local services or configuration are not healthy.
  3. Select the best available real-browser surface that holds the signed-in test session. Honor an explicitly requested browser. Prefer a user-connected browser or Chrome session for authenticated flows; use Computer Use only when a browser-specific tool cannot perform the required visible action. Use isolated Playwright only for repeatable coverage that does not require the real account.
  4. Navigate to the named environment, identify the account from rendered UI, and record the target URL, browser surface, account state, and baseline console/network condition. Do not inspect browser storage, cookies, or passwords.
  5. If the selected environment or session is not suitable, stop with the exact setup needed. Do not substitute anonymous coverage for an authenticated pass.

Read the full file on GitHub · 158 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. yesterday First seen · 158 lines · 79 tokens per session scan A b3caeb0e332f

Subscribe to this mod's changes

chaos is a skill published in the GitHub repository KeepSoftwareSimple/compass-calendar (226 stars, last pushed today), licensed MIT. It adds 79 tokens to every session and 1,596 once invoked, about $0.0003 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 2026-11-07.

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