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 boshi-xixixi/TraeSkill --skill acreadiness-assessgit clone --depth 1 https://github.com/boshi-xixixi/TraeSkillWrote 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/boshi-xixixi/traeskill/acreadiness-assess)<a href="https://agentmods.dev/skills/boshi-xixixi/traeskill/acreadiness-assess"><img src="https://agentmods.dev/badge/skills/boshi-xixixi/traeskill/acreadiness-assess/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/skills/boshi-xixixi/traeskill/acreadiness-assess"><img src="https://agentmods.dev/badge/skills/boshi-xixixi/traeskill/acreadiness-assess.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 | $0.00082 | $0.00811 |
| Opus 5 | $0.00041 | $0.00405 |
| Sonnet 5 | $0.00016 | $0.00162 |
| Haiku 4.5 | $0.00008 | $0.00081 |
Grade A, and why
acreadiness-assess 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 10d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- acreadiness-assess — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/acreadiness-assess — AI-readiness assessment
Use this skill whenever the user asks for an AI-readiness assessment, a readiness check, an audit, or wants to see how AI-ready their repository is.
This skill is the Measure step in AgentRC's Measure → Generate → Maintain loop. The result is a self-contained HTML dashboard the user can open with file:// or commit to the repo.
Steps
-
Confirm prerequisites. Node 20+ must be on PATH. If unsure, run
node --version. -
Decide on a policy (optional but encouraged):
- If the user provided
--policy <source>, capture it. - Otherwise check
agentrc.config.jsonfor apoliciesarray. - If neither, run with no policy (built-in defaults).
- For a primer on policies, suggest the
acreadiness-policyskill.
- If the user provided
-
Run the readiness scan in the repo root with structured output:
npx -y github:microsoft/agentrc readiness --json [--policy <source>] [--per-area]The
CommandResult<T>JSON envelope is your input for the next step. -
Hand off to the
ai-readiness-reportercustom agent to interpret the JSON and producereports/index.html. The agent renders via the bundled templatereport-template.html(shipped alongside this skill) so every report has an identical look & feel. The agent:- Reads the bundled
report-template.htmland substitutes placeholders with real data. - Inlines all CSS, ships a single static file (works under
file://). - Renders maturity level, overall score, grade, pass-rate vs threshold.
- Breaks down all 9 pillars across Repo Health (8) and AI Setup (1) with what it measures, why it matters for AI, current state, and a specific recommendation.
- Tags every pillar with an AI relevance badge (High / Medium / Low).
- Surfaces Extras separately (they never affect the score).
- Shows the Active Policy including any disabled/overridden criteria and thresholds.
- Produces a Prioritised Remediation Plan (🔴 Fix First / 🟡 Fix Next / 🔵 Plan).
- Embeds the raw AgentRC JSON for reuse.
- Reads the bundled
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.
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.
- 10d ago First seen · 47 lines · 82 tokens per session scan A e632ae0d57b8
acreadiness-assess is a skill published in the GitHub repository boshi-xixixi/TraeSkill (262 stars, last pushed 4mo ago), licensed MIT. It adds 82 tokens to every session and 811 once invoked, about $0.0004 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 2026-08-30.
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