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/alexmond/alexmskillsWrote 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/commands/alexmond/alexmskills/mastery)<a href="https://agentmods.dev/commands/alexmond/alexmskills/mastery"><img src="https://agentmods.dev/badge/commands/alexmond/alexmskills/mastery/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/commands/alexmond/alexmskills/mastery"><img src="https://agentmods.dev/badge/commands/alexmond/alexmskills/mastery.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 | $0.00048 | $0.00723 |
| Opus 5.5 | $0.00019 | $0.00289 |
| Sonnet 5.5 | $0.00010 | $0.00145 |
| Haiku 4.5 | $0.00005 | $0.00072 |
Grade A, and why
mastery 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.
How it starts
The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/prompt-coach:mastery
Direct top-level access to the mastery view. Same output as /prompt-coach:config mastery but you don't have to type the config prefix.
What to do
-
Resolve
scripts/config.pyfrom this plugin's root (the parent of thiscommands/directory). This works in either client's cache or a dev checkout. -
Parse the user's input:
User says Run (no arg) python3 <path> mastery"as JSON" / "json" python3 <path> --json mastery"reset " python3 <path> mastery-reset <rule-id>(dry-run first, then ask to confirm)"reset all" / "reset everything" python3 <path> --dry-run mastery-reset-all, show preview, ask to confirm -
Render the script's stdout verbatim. The output already has the analysis section built in (v0.26+): mastery evidence quality (well-tested vs barely-tested vs untested), untested masteries listed with a suggestion, and close-to-mastery rules surfaced.
-
Calibrated follow-up (≤2 sentences):
- Many untested masteries (≥5) → note that this often means the rules don't apply to how you prompt, not that you've internalized them. Suggest picking one to reset if the user wants active coverage.
- Rules close to mastery → mention them; a couple more clean prompts and they graduate.
- Zero mastered rules → first-time user; explain that mastery is
earned by demonstration: a rule masters once you actually use its good
technique (its positive detector fires)
min_demonstrationstimes (default 3) with no recent relapse — clean streaks alone no longer master a rule.
Natural-language routing
| Prompt | Route |
|---|---|
| "show mastery" / "my mastery" / "how am I doing" | mastery |
| "check my mastery" / "analyze mastery" | mastery |
| "which rules mastered" | mastery (analysis section covers it) |
| "reset " | mastery-reset <rule-id> |
| "reset all my mastery" | mastery-reset-all |
| "is any of my mastery suspicious" | mastery (analysis section flags untested) |
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 Changed · -6 lines b34cb682e5c3
- 1mo ago First seen · 66 lines · 48 tokens per session scan A 44f4291e9b54
mastery is a command published in the GitHub repository alexmond/alexmskills (10 stars, last pushed 12d ago), licensed MIT. It adds 48 tokens to every session and 723 once invoked, about $0.0002 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 2026-08-31.
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