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 wyattowalsh/agents --skill email-whizgit clone --depth 1 https://github.com/wyattowalsh/agentsWrote 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/wyattowalsh/agents/email-whiz)<a href="https://agentmods.dev/skills/wyattowalsh/agents/email-whiz"><img src="https://agentmods.dev/badge/skills/wyattowalsh/agents/email-whiz/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/wyattowalsh/agents/email-whiz"><img src="https://agentmods.dev/badge/skills/wyattowalsh/agents/email-whiz.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 | $0.00046 | $0.05942 |
| Opus 5.5 | $0.00018 | $0.02377 |
| Sonnet 5.5 | $0.00009 | $0.01188 |
| Haiku 4.5 | $0.00005 | $0.00594 |
Grade A, and why
email-whiz 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.
How it starts
The opening of the file, as written. The whole thing — 428 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Email Whiz
Gmail inbox management via MCP. Parallel-first, large-inbox optimized.
Canonical Vocabulary
| Term | Definition |
|---|---|
| 5-bucket | DO / DELEGATE / DEFER / REFERENCE / NOISE — five triage buckets (historically "4D+N") |
| inbox zero | State where inbox contains only items requiring action today |
| fast-lane | Sender/subject-only classification without reading email content |
| security gate | Subject-keyword scan of NOISE before archiving (catches 2FA, password resets) |
| session cache | Local cache of Phase 0 results (1h TTL) at `~/.{gemini |
| tier | Inbox size class: Small (<50) / Medium (50-500) / Large (500-5k) / Massive (5k+) |
| quick | Modifier prefix that skips Phase 0 for lightweight modes |
| combo | Chain two modes sharing discovered state: <mode> + <mode> |
| mega-wave | Single message with 10-15 independent tool calls bundled together |
| baseline | Rolling 30-day average inbox count; bankruptcy triggers are relative to this |
| auto-rule | Gmail filter created from behavioral pattern analysis |
| VIP | Sender who receives consistent replies and high-priority treatment |
| engagement | Reply rate to a sender: replies sent / emails received |
| confidence | HIGH >80% / MEDIUM 50-80% / LOW <50% — governs auto-rule actions |
| memory | Persistent user preferences and patterns at `~/.{gemini |
| correction | User disagreement with auto-classification, stored as a memory override |
| staleness | Memory entry not confirmed/used beyond threshold (VIP: 90d, override: 60d) |
Dispatch
$ARGUMENTS |
Action |
|---|---|
triage |
Categorize inbox with fast-lane + 5-bucket, batch process by category |
inbox-zero |
Daily/weekly routine, progress tracking, baseline bankruptcy detection |
filters |
Pattern-detected filter suggestions with confidence scoring |
auto-rules |
Behavioral analysis → auto-create Gmail filters from templates |
analytics |
Volume trends, response times, sender frequency, timing patterns |
newsletters |
Subscription audit + unsubscribe plan |
labels |
Taxonomy analysis, merge/rename/delete recommendations |
search <goal> |
Natural language → Gmail search query |
senders |
VIP + noise identification |
digest |
Recent important email summary |
cleanup |
Archive candidates, duplicate detection, batch archiving |
audit |
Full inbox health report with score and action plan |
quick search or quick digest |
Skip Phase 0, run mode directly. Only search and digest are quick-compatible |
<mode> + <mode> |
Chain modes, sharing discovered state (triage + filters) |
| (empty) | Auto-scan: run Phase 0 + account analysis, present prioritized action plan |
What ships with it
25 files 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.
- CHANGELOG.md 9.3 KB
- evals/dispatch-routing.md 7.7 KB
- evals/evals.json 5.1 KB
- references/analytics-guide.md 7.3 KB
- references/efficiency-guide.md 8.0 KB
- references/filter-patterns.md 11 KB
- references/inbox-zero-system.md 6.5 KB
- references/templates.md 9.2 KB
- references/tool-reference.md 9.0 KB
- references/triage-framework.md 9.9 KB
- references/workflows.md 8.7 KB
- scripts/asset_toolkit/__init__.py 303 B runs code
- scripts/asset_toolkit/_shared.py 5.6 KB runs code
- scripts/asset_toolkit/common.py 3.0 KB runs code
- scripts/asset_toolkit/package.py 43 KB runs code
- scripts/asset_toolkit/validate_evals.py 11 KB runs code
- scripts/asset_toolkit/validate_hooks.py 13 KB runs code
- scripts/asset_toolkit/validate_skill.py 3.6 KB runs code
- scripts/check.py 2.2 KB runs code
- scripts/constants.py 526 B runs code
- scripts/inbox_snapshot.py 8.8 KB runs code
- scripts/memory.py 22 KB runs code
- scripts/validate-skill.sh 4.8 KB runs code
- tests/test_inbox_snapshot.py 13 KB runs code
- tests/test_memory.py 37 KB runs code
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 First seen · 428 lines · 46 tokens per session scan A 81f5312e1b62
email-whiz is a skill published in the GitHub repository wyattowalsh/agents (5 stars, last pushed 1mo ago), licensed MIT. It adds 46 tokens to every session and 5,942 once invoked, about $0.0002 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 2026-09-03.
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