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/viktor-silakov/readiness/readinessnpx skills add viktor-silakov/readiness --skill readinessgit clone --depth 1 https://github.com/viktor-silakov/readinessWrote 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/viktor-silakov/readiness/readiness)<a href="https://agentmods.dev/skills/viktor-silakov/readiness/readiness"><img src="https://agentmods.dev/badge/skills/viktor-silakov/readiness/readiness.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 | $0.00033 | $0.00946 |
| Opus 5 | $0.00016 | $0.00473 |
| Sonnet 5 | $0.00007 | $0.00189 |
| Haiku 4.5 | $0.00003 | $0.00095 |
Grade A, and why
readiness 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repository Readiness Assessment
Audit any repository to determine readiness for autonomous AI agent workflows. Produces a structured report scoring 81 distinct criteria.
Target: Use $ARGUMENTS if a GitHub URL is provided, otherwise analyze the current working directory.
Workflow
- Clone if needed — When
$ARGUMENTSis a GitHub URL, clone to/tmp - Discover context — Detect languages, locate source/test/config directories
- Identify apps — Count deployable units (monorepo services, libraries, etc.)
- Evaluate criteria — Score all 81 criteria from CRITERIA.md
- Calculate level — Determine maturity level 1-5 based on thresholds
- Generate report — Output visual ASCII report per OUTPUT_FORMAT.md
- Ask about HTML export — ALWAYS ask the user if they want the D3.js dashboard after the ASCII report; do not proceed until they answer
Boundary Rules
- Stay within git repository root (where
.gitexists) - Skip
.git,node_modules,dist,build,__pycache__ - Never access paths outside the repository
Language Detection
| Language | Indicators |
|---|---|
| JS/TS | package.json, tsconfig.json, .ts/.tsx/.js/.jsx |
| Python | pyproject.toml, setup.py, requirements.txt, .py |
| Rust | Cargo.toml, .rs |
| Go | go.mod, .go |
| Java | pom.xml, build.gradle, .java |
| Ruby | Gemfile, .gemspec, .rb |
Application Discovery
An application is a standalone deployable unit:
- Independent build/deploy lifecycle
- Serves users or systems directly
- Could function as its own repository
Patterns:
- Simple repos → 1 app (root)
- Monorepos → count each deployable service
- Libraries → 1 app (the library itself)
Scoring Rules
Repository Scope (43 criteria):
- Evaluated once for entire repo
- numerator: 1 (pass), 0 (fail), null (skipped)
- denominator: always 1
Application Scope (38 criteria):
- Evaluated per-app
- numerator: count of passing apps
- denominator: total apps (N)
What ships with it
4 files 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.
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.
- 3d ago First seen · 103 lines · 33 tokens per session scan A 78a172bcd15f
readiness is a skill published in the GitHub repository viktor-silakov/readiness (2 stars, last pushed 7mo ago), licensed MIT. It adds 33 tokens to every session and 946 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…