Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add Jimmynycu/token-efficiency/plugin install token-efficiency-coachWrote 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/jimmynycu/token-efficiency/coach)<a href="https://agentmods.dev/skills/jimmynycu/token-efficiency/coach"><img src="https://agentmods.dev/badge/skills/jimmynycu/token-efficiency/coach/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/jimmynycu/token-efficiency/coach"><img src="https://agentmods.dev/badge/skills/jimmynycu/token-efficiency/coach.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 | $0.00062 | $0.00814 |
| Opus 5.5 | $0.00025 | $0.00326 |
| Sonnet 5.5 | $0.00012 | $0.00163 |
| Haiku 4.5 | $0.00006 | $0.00081 |
Grade B, and why
coach scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
`~/.claude/settings.json` pointing at a stable copy of the script. If they say yes, How it starts
The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Token-Efficiency Coach
Reads a Claude Code session transcript and coaches the user on token waste — the observable inefficiencies (uncached context, context bloat, oversized tool output, failed tool calls, output-heavy turns, wrong-tier routing, redundant reads) — with a per-finding fix and a dollar estimate. It flags waste; it never grades work quality or scores a person. The analyzer runs locally and reads only your own session log, so no prompt leaves your machine.
The report below is generated at command time by the shared engine (scripts/analyze.py),
which auto-finds the latest session for this project when no path is given, or analyzes
the path you pass as an argument.
Coach report
!python3 "${CLAUDE_PLUGIN_ROOT}/scripts/analyze.py" $ARGUMENTS
Your task
- Relay the ranked report above to the user in your own words — lead with the headline (total cost, the single biggest recoverable amount) and then the findings in priority order. Keep dollar figures framed as upper-bound estimates, exactly as the engine does. Do not invent numbers the report did not produce.
- Offer to apply the top fix. Pick the highest-severity finding and propose the
concrete remedy it implies, for example:
- Low cache hit → restructure the session so stable context (system prompt, instructions, pinned files) sits at the FRONT and stays byte-identical so it caches.
- Context bloat / very long thread → compact the conversation or split the remaining work into a fresh session to shed dead context.
- Oversized tool output / redundant reads → read targeted line ranges, grep for the lines needed, and pipe noisy commands through head/tail instead of dumping whole files.
- Everything on the priciest model → route mechanical steps (renames, greps, boilerplate, file reads) to a cheaper tier and reserve the top model for real reasoning.
- Offer to wire up the live statusline if the user does not already have one. The
plugin ships
scripts/statusline.py(live$cost · ctx tokens · cache-hit% · ⚠), but a plugin cannot register astatusLineitself — it must go in the user's~/.claude/settings.jsonpointing at a stable copy of the script. If they say yes, walk them through the README's "Wire up the statusline" steps (copy the script to a stable path, add thestatusLineblock, accept the trust dialog).
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 First seen · 57 lines · 62 tokens per session scan B 0b0846be87c8
coach is a skill published in the GitHub repository Jimmynycu/token-efficiency (3 stars, last pushed 4mo ago), licensed MIT. It adds 62 tokens to every session and 814 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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