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 avizmarlon/agent-skills --skill tokens-taxonomygit clone --depth 1 https://github.com/avizmarlon/agent-skillsWrote 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/avizmarlon/agent-skills/tokens-taxonomy)<a href="https://agentmods.dev/skills/avizmarlon/agent-skills/tokens-taxonomy"><img src="https://agentmods.dev/badge/skills/avizmarlon/agent-skills/tokens-taxonomy/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/avizmarlon/agent-skills/tokens-taxonomy"><img src="https://agentmods.dev/badge/skills/avizmarlon/agent-skills/tokens-taxonomy.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 | $0.00066 | $0.01017 |
| Opus 5 | $0.00033 | $0.00508 |
| Sonnet 5 | $0.00013 | $0.00203 |
| Haiku 4.5 | $0.00007 | $0.00102 |
Grade A, and why
tokens-taxonomy 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 11d 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Token Taxonomy — One Token Per Purpose — Hard Rule
Principle: Each API key or authentication token should have a single, well-defined purpose with a descriptive name. This is not binary ("broad vs. narrow") — it's 2–3 tokens with clearly demarcated scopes, one per category of use.
Why this matters:
- Real least privilege, not theater. A broad token in a CI workflow that leaks via logs compromises everything. A narrow token leaks only that specific purpose.
- Asymmetric blast radius. Tokens in CI/automation (GitHub Actions, scheduled workers, third-party scripts) have high leak surface. Tokens in ops (manual scripts, agent-driven tasks) live in local env vars or secure vaults — smaller surface.
- Fast revocation velocity. A CI token leaks → revoke only that one, ops continues unaffected. Without separation, any leak breaks everything.
- Zero cost. Every major platform supports multiple tokens per account; creating one takes 30 seconds.
- Industry-standard IAM pattern. AWS IAM, GCP service accounts, GitHub Apps, and enterprise OAuth scopes all follow this structure.
How to Apply
| Situation | Decision |
|---|---|
| Platform with one caller only (one manual script) | 1 token with minimal scope. Acceptable. |
| Platform with 2+ different callers (CI + agent + scheduled job + manual ops) | Separate by caller category. Minimum 2: one for CI/automation + one for ops. |
| One "universal" token used everywhere | Anti-pattern. Refactor. |
| 10+ fragmented tokens (one per workflow) | Anti-pattern. Consolidate into 2–3 categories. |
Standard Token Categories
Adjust these for your platform, but the pattern is universal:
<service>-ci-bot— deploy, trigger, release actions only. Deployed to CI/automation systems (GitHub Actions, GitLab CI, scheduled tasks, etc.).<service>-ops-bot— full read/write for operational tasks. Stored securely for manual use, agent-driven operations, sysadmin scripts.<service>-readonly-bot— read-only access. For dashboards, monitoring, audit logs. Optional; skip if not needed.
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.
- 11d ago First seen · 68 lines · 66 tokens per session scan A 0cc406f37251
tokens-taxonomy is a skill published in the GitHub repository avizmarlon/agent-skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 66 tokens to every session and 1,017 once invoked, about $0.0003 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 2026-08-31.
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