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/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/commands/ololand-ai/ololand-plugins/watchlist)<a href="https://agentmods.dev/commands/ololand-ai/ololand-plugins/watchlist"><img src="https://agentmods.dev/badge/commands/ololand-ai/ololand-plugins/watchlist/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/commands/ololand-ai/ololand-plugins/watchlist"><img src="https://agentmods.dev/badge/commands/ololand-ai/ololand-plugins/watchlist.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 | $0.00018 | $0.00385 |
| Opus 5.5 | $0.00007 | $0.00154 |
| Sonnet 5.5 | $0.00004 | $0.00077 |
| Haiku 4.5 | $0.00002 | $0.00038 |
Grade A, and why
watchlist 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.
What it actually says
Watchlist
Use this command when the user wants ongoing monitoring for a sourcing thesis, signal-driven target tracking, or promotion of a watchlist match into a deal.
Usage
/watchlist list
/watchlist create "Healthcare IT carveouts" criteria='{"query":"healthcare IT carveouts","company_scope":"both"}'
/watchlist matches <watchlist_id>
/watchlist promote <watchlist_id> <match_id>
Execution
list— callmcp__ololand__list_watchlists.create— ask for a name and criteria if absent, then callmcp__ololand__create_watchlist.matches— callmcp__ololand__list_watchlist_matches, defaulting to active/non-dismissed matches.promote— confirm the user wants to create a deal, then callmcp__ololand__promote_watchlist_match.- If the user starts from prose instead of a watchlist id, run
/company-discoveryfirst and use its filters as watchlist criteria.
Output
- For lists: watchlist name, matched count, threshold, last matched time, and criteria.
- For matches: company, match score, match reason, signal count, promoted deal id if present.
- For promote: created deal id, canonical company name, and returned
view_url.
Guardrails
- Promotion creates a real deal row. Confirm before calling
promote_watchlist_match. - Dismissal/pinning remains a UI workflow unless the user explicitly asks for match state updates.
- Watchlists are monitoring infrastructure, not diligence conclusions.
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 · 39 lines · 18 tokens per session scan A 2fcad7a36d71
watchlist is a command published in the GitHub repository ololand-ai/ololand-plugins (0 stars, last pushed 4d ago), licensed Apache-2.0. It adds 18 tokens to every session and 385 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other commands, from other repositories
analyze-bond-rv
Analyze a bond's relative value vs yield curves and credit spreads with scenario stress testing.
valuation-methods
Valuation methods analysis — multiples, DCF inputs, PEG integration, valuation assumption extraction.
merit-reconcile
Preview or check the status of Stripe → Merit payout reconciliation (read-only).
cost-per-task
Compute cost-per-successful-task unit economics from usage and cost data, including retries, failures, and quality thresholds.
audit-checklist
Perform an internal audit, review controls, or prepare for an external financial audit.
scan
Scan AWS account for cost optimization.