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 ololand-ai/ololand-plugins --skill deal-sourcinggit clone --depth 1 https://github.com/ololand-ai/ololand-pluginsWrote 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/ololand-ai/ololand-plugins/deal-sourcing)<a href="https://agentmods.dev/skills/ololand-ai/ololand-plugins/deal-sourcing"><img src="https://agentmods.dev/badge/skills/ololand-ai/ololand-plugins/deal-sourcing/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/ololand-ai/ololand-plugins/deal-sourcing"><img src="https://agentmods.dev/badge/skills/ololand-ai/ololand-plugins/deal-sourcing.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 | $0.00038 | $0.01141 |
| Opus 5 | $0.00019 | $0.00571 |
| Sonnet 5 | $0.00008 | $0.00228 |
| Haiku 4.5 | $0.00004 | $0.00114 |
Grade A, and why
deal-sourcing 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 8d 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deal Sourcing
Why this exists
Generic "sourcing" prompts produce a list of company names and end there. This skill closes the loop: discovery → durable mandate/candidates → contact graph → reviewable outreach copy → deal conversion. Persistence happens before contact capture, so a missing connector never loses the analyst's market map.
Pipeline
Thesis routing
Classify thesis intent before starting this one-off pipeline. Requests to create, list, update, deactivate, or review matches for a standing sourcing mandate must go directly to the corresponding thesis MCP operation; do not run discovery, create a watchlist, persist candidates, import contacts, or draft outreach first. A thesis is a long-lived sourcing mandate, not a SWOT or strategy framework.
1. Discovery
- Use
mcp__ololand__search_company_discoverywithmode: "discover",company_scope: "private", and explicit filters (sector, geography, size, ownership type if PE-relevant). - Cap initial set to 25 per run. Quality > quantity. If user wants more, run again with refined criteria.
2. Durable mandate and candidates
- Create or reuse a materially identical watchlist with
mcp__ololand__create_watchlist. - Pass the selected company-discovery result objects unchanged to
mcp__ololand__save_sourcing_candidates, withwatchlist_idset to the created/reused watchlist ID andcandidatesset to the selected result objects. - This is the required persistence step. The tool is idempotent and preserves discovery snapshots, source systems, evidence references, score/rationale, workflow stage, and later deal-conversion lineage.
3. Contact capture
- Inspect the company-discovery result for returned executives and actual identity evidence: email, phone number, or LinkedIn URL.
- Pick at most one contact. Priority: founder > CEO > CFO > head of corp dev.
- When supported evidence exists, import it through
mcp__ololand__openclaw_import_contactsusingsource_system: "company_discovery". This is the tenant-scoped relationship graph and central suppression/dedupe boundary. - Link the returned contact to the candidate with
mcp__ololand__update_sourcing_candidate, passing the samewatchlist_id, the saved candidatematch_id, and advancing it toenriched. - When no supported identity evidence exists, leave the candidate shortlisted and report that contact enrichment remains outstanding.
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.
- 8d ago First seen · 106 lines · 38 tokens per session scan A 82e9185f2e71
deal-sourcing is a skill published in the GitHub repository ololand-ai/ololand-plugins (0 stars, last pushed 7d ago), licensed Apache-2.0. It adds 38 tokens to every session and 1,141 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 2026-09-03.
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