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 JunMystery/Agent-Guidance-Python --skill investor-outreachgit clone --depth 1 https://github.com/JunMystery/Agent-Guidance-PythonWrote 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/junmystery/agent-guidance-python/investor-outreach)<a href="https://agentmods.dev/skills/junmystery/agent-guidance-python/investor-outreach"><img src="https://agentmods.dev/badge/skills/junmystery/agent-guidance-python/investor-outreach/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/junmystery/agent-guidance-python/investor-outreach"><img src="https://agentmods.dev/badge/skills/junmystery/agent-guidance-python/investor-outreach.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 | $0.00054 | $0.00592 |
| Opus 5.5 | $0.00022 | $0.00237 |
| Sonnet 5.5 | $0.00011 | $0.00118 |
| Haiku 4.5 | $0.00005 | $0.00059 |
Grade A, and why
investor-outreach 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.
This is a copy
98% identical to investor-outreach — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Investor Outreach
Write investor communication that is short, concrete, and easy to act on.
When to Activate
- writing a cold email to an investor
- drafting a warm intro request
- sending follow-ups after a meeting or no response
- writing investor updates during a process
- tailoring outreach based on fund thesis or partner fit
Core Rules
- Personalize every outbound message.
- Keep the ask low-friction.
- Use proof instead of adjectives.
- Stay concise.
- Never send copy that could go to any investor.
Voice Handling
If the user's voice matters, run brand-voice first and reuse its VOICE PROFILE.
This skill should keep the investor-specific structure and ask discipline, not recreate its own parallel voice system.
Hard Bans
Delete and rewrite any of these:
- "I'd love to connect"
- "excited to share"
- generic thesis praise without a real tie-in
- vague founder adjectives
- begging language
- soft closing questions when a direct ask is clearer
Cold Email Structure
- subject line: short and specific
- opener: why this investor specifically
- pitch: what the company does, why now, and what proof matters
- ask: one concrete next step
- sign-off: name, role, and one credibility anchor if needed
Personalization Sources
Reference one or more of:
- relevant portfolio companies
- a public thesis, talk, post, or article
- a mutual connection
- a clear market or product fit with the investor's focus
If that context is missing, state that the draft still needs personalization instead of pretending it is finished.
Follow-Up Cadence
Default:
- day 0: initial outbound
- day 4 or 5: short follow-up with one new data point
- day 10 to 12: final follow-up with a clean close
Do not keep nudging after that unless the user wants a longer sequence.
Warm Intro Requests
Make life easy for the connector:
- explain why the intro is a fit
- include a forwardable blurb
- keep the forwardable blurb under 100 words
Post-Meeting Updates
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 · 92 lines · 54 tokens per session scan A ab71ee37a1ff
investor-outreach is a skill published in the GitHub repository JunMystery/Agent-Guidance-Python (2 stars, last pushed 3mo ago), licensed MIT. It adds 54 tokens to every session and 592 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 98% identical to investor-outreach, differing in 2 lines, and is treated as a copy.
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