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 andreadellacorte/groove --skill groove-utilities-statsgit clone --depth 1 https://github.com/andreadellacorte/grooveWrote 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/andreadellacorte/groove/groove-utilities-stats)<a href="https://agentmods.dev/skills/andreadellacorte/groove/groove-utilities-stats"><img src="https://agentmods.dev/badge/skills/andreadellacorte/groove/groove-utilities-stats/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/andreadellacorte/groove/groove-utilities-stats"><img src="https://agentmods.dev/badge/skills/andreadellacorte/groove/groove-utilities-stats.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 | $0.00037 | $0.01401 |
| Opus 5.5 | $0.00015 | $0.00560 |
| Sonnet 5.5 | $0.00007 | $0.00280 |
| Haiku 4.5 | $0.00004 | $0.00140 |
Grade A, and why
groove-utilities-stats 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 2mo 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
groove-utilities-stats
Use $ARGUMENTS to specify the period: week (default), month, or all.
Bash fast-path
This skill has a bash script at scripts/stats.sh. Run it directly for faster, model-free execution:
bash .agents/skills/groove-utilities-stats/scripts/stats.sh week
(Pass week, month, or all to match $ARGUMENTS.) If the script exits 0, report its stdout and stop — do not continue with the steps below. If it exits non-zero, continue with the markdown steps (exit 3 means it printed the local metrics but the linear/github task counts still need to be computed below; exit 1 means no .groove/).
Outcome
A read-only dashboard is printed to the conversation quantifying compound-loop health for the period: the compound funnel (lessons captured vs graduated), adherence (daily-log coverage, streak, rollup freshness, ratings), and velocity (task open/closed, commits). No files are written. This answers "is the workflow compounding / am I keeping the rhythm" — for qualitative patterns, it points to /groove-utilities-memory-retrospective.
Acceptance Criteria
- Compound funnel shown: lessons captured (total + in period), graduated (total + in period), graduation rate
- Adherence shown: daily-log coverage over the last
memory.review_daysbusiness days, current streak, weekly/monthly rollup freshness, ratings count + average - Velocity shown: task open/closed counts (if a task backend is configured) and commit count in the period
- Output goes to the conversation only; nothing is written
- Absent data sources are skipped with sensible "n/a"/"NA" placeholders rather than errors
Steps
(Model fallback — the bash fast-path above does this deterministically. Reproduce the same output format.)
-
Memory path is always
.groove/memory/. If.groove/is absent, stop with an install hint. -
Read
.groove/index.mdfrontmatter:tasks.storage(backend; legacy keytasks.backend) andmemory.review_days(default 5).
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.
- 2mo ago First seen · 97 lines · 37 tokens per session scan A 1f4ff08b98c8
groove-utilities-stats is a skill published in the GitHub repository andreadellacorte/groove (6 stars, last pushed 3mo ago), licensed MIT. It adds 37 tokens to every session and 1,401 once invoked, about $0.0001 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.
groove-utilities-stats compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| groove-utilities-statsandreadellacorte/groove | Skill | 6 | 3mo ago | MIT | A | 37 | Claude Code |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | today | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | today | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 314k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |