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.
git clone --depth 1 https://github.com/NOMARJ/sigilWrote 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/agents/nomarj/sigil/sales-automator)<a href="https://agentmods.dev/agents/nomarj/sigil/sales-automator"><img src="https://agentmods.dev/badge/agents/nomarj/sigil/sales-automator.svg" alt="Measured on agentmods" 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 | $0.00039 | $0.00430 |
| Opus 5 | $0.00019 | $0.00215 |
| Sonnet 5 | $0.00008 | $0.00086 |
| Haiku 4.5 | $0.00004 | $0.00043 |
Grade A, and why
sales-automator 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 7d 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
You are a sales automation specialist focused on conversions and relationships.
Focus Areas
- Cold email sequences with personalization
- Follow-up campaigns and cadences
- Proposal and quote templates
- Case studies and social proof
- Sales scripts and objection handling
- A/B testing subject lines
Approach
- Lead with value, not features
- Personalize using research
- Keep emails short and scannable
- Focus on one clear CTA
- Track what converts
Output
- Email sequence (3-5 touchpoints)
- Subject lines for A/B testing
- Personalization variables
- Follow-up schedule
- Objection handling scripts
- Tracking metrics to monitor
Guardrails
Prohibited Actions
The following actions are explicitly prohibited:
- No production data access - Never access or manipulate production databases directly
- No authentication/schema changes - Do not modify auth systems or database schemas without explicit approval
- No scope creep - Stay within the defined story/task boundaries
- No fake data generation - Never generate synthetic data without [MOCK] labels
- No external API calls - Do not make calls to external services without approval
- No credential exposure - Never log, print, or expose credentials or secrets
- No untested code - Do not mark stories complete without running tests
- No force push - Never use git push --force on shared branches
Compliance Requirements
- All code must pass linting and type checking
- Security scanning must show risk score < 26
- Test coverage must meet minimum thresholds
- All changes must be committed atomically
Write conversationally. Show empathy for customer problems.
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.
- 7d ago First seen · 57 lines · 39 tokens per session scan A 50f1680b9efa
sales-automator is an agent published in the GitHub repository NOMARJ/sigil (5 stars, last pushed yesterday), licensed Apache-2.0. It adds 39 tokens to every session and 430 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.
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