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 byerlikaya/claude-starter-kit --skill token-budgetgit clone --depth 1 https://github.com/byerlikaya/claude-starter-kitWrote 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/byerlikaya/claude-starter-kit/token-budget)<a href="https://agentmods.dev/skills/byerlikaya/claude-starter-kit/token-budget"><img src="https://agentmods.dev/badge/skills/byerlikaya/claude-starter-kit/token-budget/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/byerlikaya/claude-starter-kit/token-budget"><img src="https://agentmods.dev/badge/skills/byerlikaya/claude-starter-kit/token-budget.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 | $0.00025 | $0.00960 |
| Opus 5 | $0.00013 | $0.00480 |
| Sonnet 5 | $0.00005 | $0.00192 |
| Haiku 4.5 | $0.00003 | $0.00096 |
Grade A, and why
token-budget 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 9d 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 — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Token & Context Discipline
Trigger phrases: "token budget", "token cost", "context window", "context management", "context is full", "clear context", "running out of context"
A subagent exists for context management: it runs in its own window and returns only its summary to the main thread — intermediate noise (file reads, searches, logs) never enters the main context.
Warning — measured, not guessed. Each subagent re-pays its full context from scratch: in a real
transcript the first turn was cache_read=0, every token cache_creation — nothing is shared with the main
thread's cache. A no-op subagent (task = "reply DONE") already cost ~10k tokens with restricted tools and
~16k with full tool access; that floor is base system prompt + tool schemas, paid fresh every time. Of the
always-on material only the skill listing (~2.5–3k tokens) is inherited by a subagent — the discipline
(DISCIPLINE.md/CLAUDE.md) and the agent descriptions are not injected into it. So a delegation is worth it
for isolation / parallelism / a clean window, or when the isolated work would otherwise cost the main thread
more than that ~10–16k floor — never by default.
Rules
- Output = summary. The agent returns a short, structured summary to the main thread; it does not return raw logs / file dumps / long code.
- Move to a file. Heavy output (a plan, scan report, inventory) is written to
docs/*.md; a summary + pointer comes back. (local, in gitignore) - Delegation threshold. Noisy/heavy work (reading many files, scanning, research) → subagent. A single tool-call / small work → main thread. Concretely: if the isolated work won't save the main thread more than the ~10–16k fresh-context floor a subagent costs, keep it on the main thread — delegate for isolation, not to shave a few reads.
- Least tooling. An agent holds only the tools it needs; extras accidentally pollute the context + burn the limit.
- Lean SKILL.md. Skills load into the main context; heavy reference goes to a separate file, only when needed.
- Targeted reading. Instead of reading a whole file, pinpoint with Grep/Glob.
- Manage with /context. session-manager-csk recommends continue/handoff+clear based on the real percentage; at a phase boundary,
/clear. - Bound what a command hands back. All of the rules above govern the context's own footprint; none of them
govern what a single
Bashcall dumps into it. Afindover a monorepo, an unfiltered log, a full test run — each returns everything to the main thread whether or not any of it is read. Ask for the answer, not the corpus:grep -covergrep,| tail -20over the whole file,--quiet/--porcelainwhere the tool has one, and a redirect to a file plus a pointer when the output is genuinely needed later (rule 2). - Cut what nothing reaches — with evidence, not a hunch. Every installed skill spends its name and
description in EVERY session, forever.
bash .claude/eval/utilization.shreports which skills actually fired in this project's transcripts and how many bytes the cold ones cost, which is the listdoctor.sh§4a'sskillOverrides: name-onlyadvice needs and never had. Read it as evidence, not a verdict: a skill that only fires during an incident is doing its job by existing.--all-projectswidens the scope; by default it reads this project only and prints names and counts, never paths or content.
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.
- 9d ago First seen · 45 lines · 25 tokens per session scan A 02398870610c
token-budget is a skill published in the GitHub repository byerlikaya/claude-starter-kit (22 stars, last pushed today), licensed MIT. It adds 25 tokens to every session and 960 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 2026-09-03.
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