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 suxrobGM/jobpilot --skill scan-inboxgit clone --depth 1 https://github.com/suxrobGM/jobpilotWrote 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/suxrobgm/jobpilot/scan-inbox)<a href="https://agentmods.dev/skills/suxrobgm/jobpilot/scan-inbox"><img src="https://agentmods.dev/badge/skills/suxrobgm/jobpilot/scan-inbox/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/suxrobgm/jobpilot/scan-inbox"><img src="https://agentmods.dev/badge/skills/suxrobgm/jobpilot/scan-inbox.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 6 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 Prompt Injection · line 48 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 50 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 51 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 52 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 53 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Data Exfiltration · line 94 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00034 | $0.01352 |
| Opus 5.5 | $0.00014 | $0.00541 |
| Sonnet 5.5 | $0.00007 | $0.00270 |
| Haiku 4.5 | $0.00003 | $0.00135 |
Grade A, and why
scan-inbox 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 26d 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scan Inbox - Review Pending Email
Classify recent email and link each thread to an existing Application when there's a confident match. This skill does not write ApplicationEvent rows or mutate Application.status directly - the user approves from /inbox. One server-side exception: a rejected classification sent with reviewStatus: "auto" is applied on arrival (see Phase 4 rules).
Setup
Follow ../_shared/setup.md.
Phase 1: Confirm Mailbox Connected
jobpilot-api GET /api/email/account
If .connected === false, stop:
No email account is connected. Open
/profile→ Email and connect a Gmail account, then re-runscan-inbox.
Phase 2: Pick the Queue
One message - an id was passed (a re-scan from the inbox table). Fetch just it and classify it again even if it's already classified or reviewed:
jobpilot-api GET "/api/email/messages/<id>"
All pending - no argument. Sync, then pull the unscanned queue:
jobpilot-api POST /api/email/sync
jobpilot-api GET /api/email/messages --query reviewStatus=pending --query classification=null
Both list routes answer {items, pagination}; read .items. If it is empty: "Inbox is already reviewed. Nothing new to classify." and exit.
The rest of the skill runs over whatever you fetched. A re-scan overwrites the classification and resets reviewStatus, but never undoes an approved status move.
Phase 3: Classify
For each message, pick one classification:
| Classification | When |
|---|---|
interviewing |
Recruiter reply, interview invite, scheduling, take-home, next-round. |
rejected |
Explicit rejection / "moved forward with other candidates". |
offer |
Formal job offer (comp, start date, offer letter attached). |
verification |
One-time code, magic link, "confirm your email", 2FA from a job board. |
irrelevant |
Job alerts, digests, "jobs you may like", "you appeared in N searches", newsletters, "application received" auto-acknowledgements, marketing, calendar pings. |
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.
- 26d ago Changed · -4 lines 95b1715c1375
- 1mo ago First seen · 126 lines · 34 tokens per session scan A 026f69200ef7
scan-inbox is a skill published in the GitHub repository suxrobGM/jobpilot (101 stars, last pushed 19d ago), licensed MIT. It adds 34 tokens to every session and 1,352 once invoked, about $0.0001 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.
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