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/ppgranger/token-saver/token-saver-statsgit clone --depth 1 https://github.com/ppgranger/token-saverWrote 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/ppgranger/token-saver/token-saver-stats)<a href="https://agentmods.dev/commands/ppgranger/token-saver/token-saver-stats"><img src="https://agentmods.dev/badge/commands/ppgranger/token-saver/token-saver-stats.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 | $0.00010 | $0.00132 |
| Opus 5 | $0.00005 | $0.00066 |
| Sonnet 5 | $0.00002 | $0.00026 |
| Haiku 4.5 | $0.00001 | $0.00013 |
Grade A, and why
stats scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Run the token-saver stats command to display savings:
token-saver stats
If the token-saver CLI is not in PATH, use the bundled wrapper script (not
src/cli.py directly — it imports via the src package and needs the repo
root on sys.path, which only bin/token-saver sets up):
python3 "${CLAUDE_PLUGIN_ROOT}/bin/token-saver" stats
Present a summary of tokens saved in the current session and overall.
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.
- 5d ago First seen · 21 lines · 10 tokens per session scan A 4ef4be37aae8
stats is a command published in the GitHub repository ppgranger/token-saver (142 stars, last pushed 17d ago), licensed Apache-2.0. It adds 10 tokens to every session and 132 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 2026-08-30.
Other commands, from other repositories
psql-query
Run ad-hoc PostgreSQL analytics queries against dev/test database.
pr
Prepare and open a pull request the senior way: gate, template, scrubbed, everything visible.
plan
Turn an approved spec into an implementation plan an engineer with zero context could execute — with a quality controller that blocks placeholders and hollow tasks.
simplify
The over-engineering review: five tags (delete, stdlib, native, yagni, shrink), a mandatory replacement per finding, and a real null result when there is nothing to cut.
audit
Onboard an existing codebase: every domain's checks over the whole tree, then a triaged plan to bring it in line.
git
The pre-finish status: branch, hygiene findings, message checks, workflow lint, template state.