Borrowing it
Nothing to install: this file belongs to vagkaratzas/token-saviour. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/vagkaratzas/token-saviour/main/AGENTS.mdgit clone --depth 1 https://github.com/vagkaratzas/token-saviourWrote 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/instructions/vagkaratzas/token-saviour/agents-md)<a href="https://agentmods.dev/instructions/vagkaratzas/token-saviour/agents-md"><img src="https://agentmods.dev/badge/instructions/vagkaratzas/token-saviour/agents-md/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/instructions/vagkaratzas/token-saviour/agents-md"><img src="https://agentmods.dev/badge/instructions/vagkaratzas/token-saviour/agents-md.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 | $0.00575 | $0.00575 |
| Opus 5.5 | $0.00230 | $0.00230 |
| Sonnet 5.5 | $0.00115 | $0.00115 |
| Haiku 4.5 | $0.00057 | $0.00057 |
Grade A, and why
token-saviour AGENTS.md 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.
What it actually says
token-saviour — spend tokens where they matter
Always-on rules for agents that read AGENTS.md (Codex CLI/app, VS Code Codex extension, and
other instruction-only hosts). Full playbook with commands and evidence:
skills/token-saviour/SKILL.md.
Token cost has four independent layers; a different tool owns each. Before acting, ask:
"which layer is this task spending tokens on?" — then use that layer's tool if it is installed.
Never pretend a tool ran; if it's missing, fall back to plain Read/Grep/Bash (installs:
skills/token-saviour/references/tool_links.md).
| When you're about to… | Use instead | Layer |
|---|---|---|
cat/read several files to find a symbol, callers, a call path, or explain a module |
serena MCP tools: get_symbols_overview, find_symbol, find_referencing_symbols (it also edits: replace_symbol_body, rename_symbol) |
code-read input |
run a noisy command — tests, build, lint, git, grep, find, big listings |
rtk proxies: rtk test <cmd>, rtk grep, rtk read, rtk find, rtk git … |
command-output input |
| write a long, chatty prose reply | caveman terse mode (keep code, commands, errors, ordered/irreversible steps verbatim) | prose output |
| generate/edit a chunk of code | Ponytail rules: YAGNI, stdlib first, no unrequested abstractions, delete over add, one runnable check | code output |
| a tiny one-file/one-line lookup | plain Read/Grep/Bash — tool overhead beats the benefit | — |
Rules of thumb (all benchmark-measured; see skills/token-saviour/references/benchmark_results.md):
- Code reads dominate the bill (~88%); switching them to serena is the highest-value move (−66% alone; the full stack measured −70%).
- One tool per layer. Never run two code-read tools; never use rtk for comprehension (~0% there); never use caveman on code or Ponytail on prose (each ~0% outside its lane).
- If a loop is dominated by test runs and Pare's MCP servers are wired in, its structured
pytestbeats rtk on that one command (−72%); rtk still owns the layer overall. - Announce what you used, one line:
🪙 token-saviour: serena + rtk + caveman(orplain tools (fallback)).
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 · 30 lines · 575 tokens per session scan A f17657e3a837
token-saviour AGENTS.md is an instructions file published in the GitHub repository vagkaratzas/token-saviour (12 stars, last pushed 3mo ago), licensed MIT. It adds 575 tokens to every session, about $0.0023 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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