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 w95/awesome-claude-corporate-skills --skill compose-outreachgit clone --depth 1 https://github.com/w95/awesome-claude-corporate-skillsWrote 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/w95/awesome-claude-corporate-skills/compose-outreach)<a href="https://agentmods.dev/skills/w95/awesome-claude-corporate-skills/compose-outreach"><img src="https://agentmods.dev/badge/skills/w95/awesome-claude-corporate-skills/compose-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/w95/awesome-claude-corporate-skills/compose-outreach"><img src="https://agentmods.dev/badge/skills/w95/awesome-claude-corporate-skills/compose-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 | $0.00045 | $0.01181 |
| Opus 5 | $0.00023 | $0.00590 |
| Sonnet 5 | $0.00009 | $0.00236 |
| Haiku 4.5 | $0.00005 | $0.00118 |
Grade A, and why
compose-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 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.
This is a copy
100% identical to compose-outreach — 0 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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Compose Outreach
Generate three personalized outreach formats — email, call script, and LinkedIn message — grounded in Common Room signals for a specific company or contact.
Outreach Process
Step 1: Look Up the Target
Use Common Room MCP tools to find and retrieve data for the target (company and/or specific contact). Pull:
- Recent product activity and engagement signals
- Community activity (posts, questions, reactions)
- 3rd-party intent signals (job postings, news, funding)
- Relationship history (prior contact, meetings, email opens)
If the user specified a person, run contact-level research. If only a company was given, identify the best contact to target based on title, engagement, and role.
Step 2: Web Search for External Hooks (If CR Signals Are Thin)
If CR returned strong signals (recent activity, engagement, product usage), those should drive personalization — skip web search. If CR signals are thin or the prospect has little CR activity, run a web search for external hooks:
What to search:
"[company name]" funding OR acquisition OR launch OR announcement— last 30 days"[contact full name]" "[company name]"— look for recent articles, interviews, LinkedIn posts, or conference talks
Prioritize external hooks that are:
- Very recent (< 2 weeks) — the prospect is likely still thinking about it
- Publicly visible — they know you could have seen it
- Change-signaling — growth, new role, new product, new market
If the user explicitly asks for web search or external hooks, run it regardless of CR signal richness.
Step 3: Spark Enrichment (If Available)
If Spark is available, run enrichment on the target contact to get persona classification, background, and influence signals. Use this to calibrate tone and message angle.
Step 4: Identify the Best Hooks
From the signal data, identify the 1–3 strongest personalization hooks. Rank by:
- Recency — happened in the last 7–14 days
- Specificity — a concrete action they took, not a general trend
- Relevance — connects directly to a value your product delivers
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 · 136 lines · 45 tokens per session scan A 6bba827598fc
compose-outreach is a skill published in the GitHub repository w95/awesome-claude-corporate-skills (198 stars, last pushed 6mo ago), licensed MIT. It adds 45 tokens to every session and 1,181 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to compose-outreach, differing in 0 lines, and is treated as a copy.
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