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 common-room/claude-plugin --skill prospectgit clone --depth 1 https://github.com/common-room/claude-pluginWrote 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/common-room/claude-plugin/prospect)<a href="https://agentmods.dev/skills/common-room/claude-plugin/prospect"><img src="https://agentmods.dev/badge/skills/common-room/claude-plugin/prospect/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/common-room/claude-plugin/prospect"><img src="https://agentmods.dev/badge/skills/common-room/claude-plugin/prospect.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 | $0.00056 | $0.01299 |
| Opus 5.5 | $0.00022 | $0.00520 |
| Sonnet 5.5 | $0.00011 | $0.00260 |
| Haiku 4.5 | $0.00006 | $0.00130 |
Grade A, and why
prospect 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
100% identical to prospect — 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prospecting
Build targeted account and contact lists using Common Room's Prospector. Supports iterative refinement through natural conversation, intent-based discovery, and both net-new prospecting and signal-based queries against existing accounts.
Critical Distinction: Two Object Types
Common Room's Prospector operates against two fundamentally different object types. Always clarify which one is in play before running a query:
ProspectorOrganization — Companies not yet in Common Room
- Net-new companies that match specified criteria
- Available fields are firmographic only: name, domain, size, industry, capital raised, annual revenue, location
- Fewer filter options — no signal-based filters, no scores, no activity history
- Use when: building a brand-new target list, territory planning, top-of-funnel expansion
Organization (in Common Room) — Companies already in your CR workspace
- Full signal data available: product usage, community activity, CRM fields, scores, custom fields
- Much richer filter set — includes signal-based, score-based, segment-based, and firmographic filters
- Use when: finding warm accounts to prioritize, identifying expansion candidates, surfacing intent signals within existing pipeline
When a user's request could apply to both (e.g., "Show companies hiring AI engineers this month"), clarify:
"Are you looking for net-new companies not yet in Common Room, or filtering accounts already in your workspace?"
The catalog should make this distinction explicit so the LLM can select the right Prospector endpoint.
Step 0: Load User Context (Me)
Fetch the Me object to get the user's segments. When prospecting against Organization records (accounts already in CR), default to filtering within "My Segments" unless the user asks for a broader search.
Step 1: Gather Targeting Criteria
If criteria are already provided, proceed. Otherwise ask:
"What kind of accounts or contacts are you looking for? For example: company size, industry, job titles, signals like recent product activity or community engagement, geographic region, or specific intent signals like recent funding or job postings."
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.
- 1mo ago First seen · 100 lines · 56 tokens per session scan A 52f94d6084af
prospect is a skill published in the GitHub repository common-room/claude-plugin (3 stars, last pushed 8mo ago), licensed Apache-2.0. It adds 56 tokens to every session and 1,299 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to prospect, differing in 0 lines, and is treated as a copy.
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