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 meltedinhex/analyst-ai-pack --skill pivoting-on-iocs-across-data-sourcesgit clone --depth 1 https://github.com/meltedinhex/analyst-ai-packWrote 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/meltedinhex/analyst-ai-pack/pivoting-on-iocs-across-data-sources)<a href="https://agentmods.dev/skills/meltedinhex/analyst-ai-pack/pivoting-on-iocs-across-data-sources"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/pivoting-on-iocs-across-data-sources/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/meltedinhex/analyst-ai-pack/pivoting-on-iocs-across-data-sources"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/pivoting-on-iocs-across-data-sources.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 | $0.00076 | $0.00662 |
| Opus 5 | $0.00038 | $0.00331 |
| Sonnet 5 | $0.00015 | $0.00132 |
| Haiku 4.5 | $0.00008 | $0.00066 |
Grade A, and why
pivoting-on-iocs-across-data-sources 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.
What it actually says
Pivoting on IOCs Across Data Sources
When to Use
- You have a seed set of IOCs (IPs, domains, hashes, URLs) and multiple log sources, and you want to find co-occurring indicators, affected hosts, and the activity timeframe.
- You are expanding an investigation from initial indicators to the full scope.
Do not use raw, undeduplicated matching that floods on common indicators — anchor pivots on the specific seed set and report co-occurrence, not every mention.
Prerequisites
- A seed IOC list and one or more log sources (CSV/JSON) containing indicator fields.
Workflow
Step 1: Match seeds and gather co-occurrence
python scripts/analyst.py pivot --seeds iocs.txt --logs events.csv
Finds log records matching any seed IOC, then reports the hosts, additional indicators, and time range co-occurring with the seeds.
Step 2: Rank new indicators
Surface newly co-occurring indicators (not in the seed set) ranked by how often they appear alongside seeds — candidates to add to the IOC set.
Step 3: Confirm and expand
Validate promising new indicators and re-run the pivot to widen scope iteratively.
Step 4: Document
Record matched hosts, the timeframe, and the expanded indicator set; defang in output.
Validation
- Matches are anchored to the seed IOC set.
- Co-occurring hosts/indicators and the time range are reported.
- New indicators are ranked by co-occurrence with seeds; output is defanged.
Pitfalls
- Common indicators (shared CDNs, OS update hosts) inflating co-occurrence — exclude allow-listed.
- Field/format mismatches (IP vs CIDR, defanged vs plain) missing matches.
- Time-zone inconsistencies skewing the activity window.
References
- See
references/api-reference.mdfor the pivot tool. - Pyramid of Pain and ATT&CK references (linked in frontmatter).
What ships with it
3 files 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.
- 8d ago First seen · 85 lines · 76 tokens per session scan A 32a2ba4e1fe3
pivoting-on-iocs-across-data-sources is a skill published in the GitHub repository meltedinhex/analyst-ai-pack (22 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 76 tokens to every session and 662 once invoked, about $0.0004 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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