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 itallstartedwithaidea/agent-skills --skill proactive-intelligencegit clone --depth 1 https://github.com/itallstartedwithaidea/agent-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/itallstartedwithaidea/agent-skills/proactive-intelligence)<a href="https://agentmods.dev/skills/itallstartedwithaidea/agent-skills/proactive-intelligence"><img src="https://agentmods.dev/badge/skills/itallstartedwithaidea/agent-skills/proactive-intelligence/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/itallstartedwithaidea/agent-skills/proactive-intelligence"><img src="https://agentmods.dev/badge/skills/itallstartedwithaidea/agent-skills/proactive-intelligence.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 | $0.02784 |
| Opus 5.5 | $0.00015 | $0.01114 |
| Sonnet 5.5 | $0.00008 | $0.00557 |
| Haiku 4.5 | $0.00004 | $0.00278 |
Grade A, and why
proactive-intelligence 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.
How it starts
The opening of the file, as written. The whole thing — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Proactive Intelligence
Part of Agent Skills™ by googleadsagent.ai™
Description
Proactive Intelligence enables agents to autonomously seek out external information — web searches, API re-pulls, data freshness checks — during analysis without waiting for explicit user requests. Traditional reactive agents only work with the data provided to them. Proactive agents recognize when their current context is insufficient, stale, or contradictory, and take independent action to fill knowledge gaps. This transforms the agent from a passive processor into an active investigator that delivers more accurate, more current, and more comprehensive results.
This skill is modeled on the search_web tool integration in the Buddy™ agent at googleadsagent.ai™, where the agent autonomously searches for competitor data, industry benchmarks, recent Google Ads policy changes, and platform updates when it detects that such information would improve its analysis. When Buddy™ encounters a campaign strategy it hasn't seen before, or metrics that deviate significantly from expected ranges, it proactively searches for context rather than speculating. This behavior is triggered by explicit conditions, not random curiosity, ensuring the additional latency and cost are justified.
The proactive intelligence framework operates on a trigger-search-integrate cycle: the agent evaluates trigger conditions during analysis, dispatches targeted searches when conditions are met, scores the relevance and freshness of results, and integrates verified findings into its ongoing reasoning. Confidence scoring ensures the agent distinguishes between well-supported conclusions and speculative ones.
Use When
- The agent analyzes data that may be affected by recent external changes (policy updates, market shifts)
- Competitive intelligence is needed alongside internal data analysis
- The agent encounters unexpected patterns that need external context to explain
- Data freshness is critical and the provided data may be outdated
- Industry benchmarks or best practices are needed to contextualize performance
- The agent must fact-check its own assumptions against current sources
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 · 267 lines · 38 tokens per session scan A d002693a0b0f
proactive-intelligence is a skill published in the GitHub repository itallstartedwithaidea/agent-skills (44 stars, last pushed 6mo ago), licensed MIT. It adds 38 tokens to every session and 2,784 once invoked, about $0.0002 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 2026-08-30.
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