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 commands/xsovad06/sova/agent-readinessgit clone --depth 1 https://github.com/xsovad06/sovaWhat 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 | $0.00016 | $0.01419 |
| Opus 5 | $0.00008 | $0.00709 |
| Sonnet 5 | $0.00003 | $0.00284 |
| Haiku 4.5 | $0.00002 | $0.00142 |
Grade A, and why
agent-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 2d 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 — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Assess the current repository's readiness for AI-assisted development, then offer to improve it step by step. $ARGUMENTS
Whenever you need to ask the user a question, always use the AskUserQuestion tool -- never ask as plain text.
When a step involves a discussion with the user, tell them they can say "done" or "skip" to move on to the next step.
Step 1. Assess (before)
Present this explanation:
This skill helps you build a layered documentation system for AI-assisted development. Each file has a distinct role:
docs/*-guidelines.md-- Detailed, domain-specific playbooks (security, testing, database, etc.) with concrete rules agents followAGENTS.md-- The onboarding doc for any AI agent: cross-cutting conventions + an index pointing to the guideline filesCLAUDE.md-- A thin, Claude Code-specific layer that imports AGENTS.md and adds Claude-only behavior (build commands, etc.).coderabbit.yaml-- Points CodeRabbit (AI code reviewer) to the guideline files so it enforces your conventions during PR reviewsREADME.md-- The front door: high-level project context for humans and agents alikeCONTRIBUTING.md-- Contribution conventions for both humans and agentsdocs/ARCHITECTURE.md-- Institutional knowledge about the system's design and key architectural decisionsWe'll check what's already in place, then walk through each file step by step.
Check every requirement and present results:
| # | Requirement | How to check |
|---|---|---|
| 1 | Domain-specific guideline files (docs/*-guidelines.md) |
Glob for files -- pass if at least one exists |
| 2 | AGENTS.md with AI-specific guidance and docs index | Check repo root |
| 3 | CLAUDE.md imports AGENTS.md (@AGENTS.md) |
Check repo root |
| 4 | CodeRabbit configured (.coderabbit.yaml) |
Check for knowledge_base.code_guidelines.filePatterns |
| 5 | README.md with foundational context | Check repo root |
| 6 | CONTRIBUTING.md with contribution conventions | Check repo root |
| 7 | docs/ARCHITECTURE.md with institutional knowledge | Check for file |
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.
- 2d ago First seen · 142 lines · 16 tokens per session scan A 672e8477a151
agent-readiness is a command published in the GitHub repository xsovad06/sova (2 stars, last pushed 2d ago), licensed Apache-2.0. It adds 16 tokens to every session and 1,419 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 2026-08-31.
Other commands, from other repositories
create-command
Create a new obsidian-second-brain command via interview - zero markdown editing required.
obsidian-architect
Scan a codebase and write a maintained set of architecture notes into the vault - overview, per-module notes, key decisions. Re-run to refresh without clobbering your edits.
obsidian-visualize
Generate a visual canvas map of your vault - see the shape of your second brain and how knowledge connects.
obsidian-export
Export a clean structured snapshot of the vault that any agent or tool can consume - flat JSON, markdown index, or an OKF (Open Knowledge Format) bundle.
obsidian-retrieval-eval
Measure how well vault search finds the right note for a natural-language question - recall@k and MRR, with the concrete failures.
obsidian-reindex
Refresh the vault's semantic search index and report coverage before and after.