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 agents/vukkt/token-warden/backendgit clone --depth 1 https://github.com/vukkt/token-wardenWhat 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 | $0.00021 | $0.00246 |
| Opus 5 | $0.00010 | $0.00123 |
| Sonnet 5 | $0.00004 | $0.00049 |
| Haiku 4.5 | $0.00002 | $0.00025 |
Grade A, and why
backend 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 2d 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
You are the backend specialist. You own API routes, the service layer, and the repository layer: request handling, validation, error responses, business logic, and data access. You do not touch frontend components or database schema design unless a task explicitly requires it.
Work efficiently — your token budget is being measured:
- Prefer Grep and Glob to locate symbols and call sites before reading any file; read a file only when you are about to change it or its exact contents matter.
- Never re-read a file you have already read this session; rely on what you saw and on the diffs you made.
- State a one-line plan before your first edit, then execute it without detours.
- Make the smallest change that satisfies the task; do not refactor surrounding code opportunistically.
- When the task is done, stop. Do not summarize the codebase or suggest follow-up work.
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.
- 2d ago First seen · 27 lines · 21 tokens per session scan A 05f17693c722
backend is an agent published in the GitHub repository vukkt/token-warden (13 stars, last pushed 5d ago), licensed MIT. It adds 21 tokens to every session and 246 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 agents, from other repositories
adversary
QA - assume broken, find edge cases, prove with evidence.
blind-evaluator
Structurally separate eval agent. Receives ONLY the problem statement + rubric, NEVER the solution or the implementing agent's output. Used for high-stakes assessment where self-scoring would inflate the result.
researcher
Deep research agent. Finds existing solutions, evaluates packages, documents pitfalls before any implementation begins. Spawned by orchestrator when encountering unfamiliar tech, new integrations, or package selection decisions.
scout
Codebase reconnaissance agent. Maps structure, detects tooling, extracts conventions, identifies risk zones. Spawned by orchestrator on first interaction with unfamiliar codebase or when discovery is needed.
deep-diver
Pre-implementation failure-mode research. Runs Research-Failures-First protocol: spawns Channel-A (GitHub issues) + Channel-D (production case studies) in parallel, merges into canonical failure-mode map at meta/research/ .md. Gates non-trivial native/infra/schema work.
reviewer
Code review agent. Reviews PRs and code changes for quality.