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 shuaiyuan17/tomo --skill systemgit clone --depth 1 https://github.com/shuaiyuan17/tomoWrote 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/shuaiyuan17/tomo/system)<a href="https://agentmods.dev/skills/shuaiyuan17/tomo/system"><img src="https://agentmods.dev/badge/skills/shuaiyuan17/tomo/system/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/shuaiyuan17/tomo/system"><img src="https://agentmods.dev/badge/skills/shuaiyuan17/tomo/system.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 68 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
- medium Output Handling · line 73 Output size or generation rate is not bounded. Unbounded output enables denial-of-service through resource exhaustion, log flooding, or context-window stuffing.Fix: Set explicit limits on output length, generation count, and rate. Use max_tokens and truncation to prevent unbounded output.
- medium Excessive Agency · line 119 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Agent Snooping · line 128 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00044 | $0.03087 |
| Opus 5 | $0.00022 | $0.01543 |
| Sonnet 5 | $0.00009 | $0.00617 |
| Haiku 4.5 | $0.00004 | $0.00309 |
Grade A, and why
tomo-system 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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tomo System Reference
Status and Health
tomo status # Is daemon running? PID, uptime
tomo logs -n 20 # Recent log entries
tomo logs -n 50 | grep ERROR # Recent errors
Sessions
tomo sessions list # All sessions with stats (queries, cost, context usage)
tomo sessions clear # Unlink all sessions (30-day TTL before deletion)
tomo sessions clear <key> # Unlink specific session (e.g. "telegram:12345")
Session stats show:
- Queries: total API calls in this session
- Cost: cumulative USD spent
- Tokens: total input/output tokens
- Context: current context window usage (X/200000)
Note: Context stats come from the SDK API and reflect the state at the end of the previous query. After compacting or other changes, you need to wait for a new query to complete before the numbers update.
Per-session model overrides live in sessionModelOverrides in ~/.tomo/config.json. Users can set them from chat with /model <name>; Tomo persists the override for the current session, closes the live SDK process, and uses the selected model on the next turn. Claude aliases, direct model IDs such as claude-sonnet-5, and LiteLLM provider/model names such as chatgpt/gpt-5.5 are accepted. tomo config can also set or clear model overrides from the Sessions menu.
When context crosses the nudge threshold (default 70%, set via lcm.nudgeAtPct in config.json), the harness sends a system message asking you to run tomo lcm daily — see the tomo-lcm skill. A second nudge at 80% asks you to use the lcm compact skill before the next user message. A periodic rollup runner also nudges you when daily/weekly/monthly/yearly blocks are due. Group sessions default to SDK auto-compact instead (override with lcm.groupCompactStyle: "lcm" to enroll groups in all three nudges).
Cron Jobs
Schedule reminders and recurring tasks via the tomo-internal MCP tools:
schedule_create— create a one-shot or recurring job (scheduleacceptsin 20m,every 6h, or a 5-field cron expression;sessionKeycontrols where the fired message lands)schedule_list— list every job withid,nextRunAt,lastStatus, etc.schedule_remove— delete byid
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 190 lines · 44 tokens per session scan A c9475763608c
tomo-system is a skill published in the GitHub repository shuaiyuan17/tomo (5 stars, last pushed today), licensed MIT. It adds 44 tokens to every session and 3,087 once invoked, about $0.0002 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.
Other skills, from other repositories
debug-optimize-lcp
Guides debugging and optimizing Largest Contentful Paint (LCP) using Chrome DevTools MCP tools. Use this skill whenever the user asks about LCP performance, slow page loads, Core Web Vitals optimization, or wants to understand why their page's main content takes too long to appear. Also use when the user mentions…
systematic-debugging
Use when debugging a failing test, build error, or runtime issue that isn't immediately obvious. Guides a 4-phase root cause analysis instead of random fix attempts.
diagnose
Trace from a reproduced symptom to the source code that causes it. Pin the specific file and approximate line, rate confidence in the cause and clarity of the fix independently, and always propose a concrete fix.
repro-admin
Reproduce an EmDash admin UI bug. Attach a container, start the demo dev server, drive the admin with agent-browser using the dev-bypass session, and capture the reproduction as screenshots plus a replayable transcript.
log-error-digest
Analyze log files to troubleshoot errors, identify peak error periods, and produce error clustering, frequency statistics, and time distribution reports. Supports JSON, syslog, and Nginx formats with automatic detection. Use when a user uploads a .log file and asks to analyze errors, find patterns, debug issues, or…
byted-util-volcengine-detect-retry
An orchestration workflow for Volcengine Cloud Detect, a service that checks websites or network endpoints from test locations.