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 Shweta-Mishra-ai/tokenmizer --skill resumegit clone --depth 1 https://github.com/Shweta-Mishra-ai/tokenmizerWrote 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/shweta-mishra-ai/tokenmizer/resume)<a href="https://agentmods.dev/skills/shweta-mishra-ai/tokenmizer/resume"><img src="https://agentmods.dev/badge/skills/shweta-mishra-ai/tokenmizer/resume/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/shweta-mishra-ai/tokenmizer/resume"><img src="https://agentmods.dev/badge/skills/shweta-mishra-ai/tokenmizer/resume.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00086 | $0.00472 |
| Opus 5.5 | $0.00034 | $0.00189 |
| Sonnet 5.5 | $0.00017 | $0.00094 |
| Haiku 4.5 | $0.00009 | $0.00047 |
Grade A, and why
resume 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
Load a previous session from TokenMizer graph memory.
Session ID
Do not ask for one. The first word of $ARGUMENTS is the session ID. If
$ARGUMENTS is empty, TokenMizer derives the ID from the working directory
name, the same way checkpoint does, and prints the ID it chose.
Ask only if the command exits 2, which means the directory has no usable name
to derive from. Then ask exactly: Which session ID should I resume?
Level
The second word of $ARGUMENTS, if present:
| Level | Size | Contents |
|---|---|---|
critical |
~100 tokens | open blockers and key decisions only |
standard |
~300 tokens | the default |
full |
~600 tokens | adds environment, schemas, endpoints |
What to do
tokenmizer resume $ARGUMENTS
Then inject the returned resume context as a system message at the top of the conversation, never as a user message, in this wrapper:
[TokenMizer — session: {session_id}]
{resume_context}
[End of session context — continue from here]
Output
Report in exactly this shape:
Resumed auth-service — 247 tokens, standard
Next: implement the token refresh endpoint
Take Next from the resume context's continue line. If it has none, omit the
line rather than inventing one. Add no commentary, and do not address the
operator by name.
If no checkpoint is found
The command exits 1 and prints what happened. Relay that, then:
Nothing saved for auth-service yet. Save the current session first:
tokenmizer checkpoint auth-service
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 Changed · +13 lines 79cb85cd54d0
- 1mo ago First seen · 50 lines · 86 tokens per session scan A e9731ab026f5
resume is a skill published in the GitHub repository Shweta-Mishra-ai/tokenmizer (34 stars, last pushed 3d ago), licensed MIT. It adds 86 tokens to every session and 472 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
cdb-scan
Map this codebase into project memory — a code graph of every symbol and how they connect, plus a written profile of stack, layout, conventions and workflows. Re-run any time to refresh both in place. Use when memory is newly installed on an existing project, or when the project has changed enough that the stored map…
handoff
Write a short handoff note for the next chat or a teammate, with what is done, what is open, what comes next and what was rejected and why. Saves it to project memory so the next chat sees it at the start, and prints it so it can be pasted into a message or a pull request. Use when the user ends a piece of work…
catchup
Answer "where did I stop?" for this project. Gives three short groups, done, open and next, taken from the last chat, the recorded to-dos, the last handoff note and git. Use when the user comes back to a project, starts a new chat, or asks where they left off. It writes nothing.
session-log
USE WHEN ending a substantial working session — user says "thanks/tomorrow/wrap up", or session shipped 3+ commits with no log today, or user asks for a summary. Distills the conversation into docs/sessions/YYYY-MM-DD- .md (context, what was done, key decisions, open questions, next steps). Hard cap 80 lines.…
pickup
Resume work on this project after an interruption or at the start of a new session: show recent wins, what was being done, the next action, and open decisions, in that order, then stop. Trigger only on an explicit /squirrel:pickup invocation, or an explicit request to resume or pick up this project's past work at the…
claude-bridge-role-memory-keeper
Playbook for a Claude Code agent in the dedicated memory keeper role — single-writer for shared agent memory across a team of 3+ peers. Use when you are designated as the keeper (= other peers send you write candidates, you write them and watch for drift). Memory hygiene + reconciliation against the canon + drift…