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 kdr/overcast --skill overcast-connect-the-dotsgit clone --depth 1 https://github.com/kdr/overcastWrote 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/kdr/overcast/overcast-connect-the-dots)<a href="https://agentmods.dev/skills/kdr/overcast/overcast-connect-the-dots"><img src="https://agentmods.dev/badge/skills/kdr/overcast/overcast-connect-the-dots/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/kdr/overcast/overcast-connect-the-dots"><img src="https://agentmods.dev/badge/skills/kdr/overcast/overcast-connect-the-dots.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00060 | $0.00998 |
| Opus 5 | $0.00030 | $0.00499 |
| Sonnet 5 | $0.00012 | $0.00200 |
| Haiku 4.5 | $0.00006 | $0.00100 |
Grade A, and why
overcast-connect-the-dots 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 10d 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
overcast-connect-the-dots
Use this skill to "connect the dots": render the whole case as one relational graph
and find the links that tie records, people, devices, places, and entities
together. This is the relational/entity board; the visual crop corkboard is
overcast-crime-board (faces + object crops with red string). Use the broad
overcast skill and overcast/reference/verbs.md for exact flags.
Workflow
- Build the graph and read the hubs.
graphemits ONE self-contained interactive HTML force-graph — records, shared-media hubs, targets, accepted/open findings, cluster people, device fingerprints, places, and regex-harvested typed entities (email / phone / @handle / url / domain / hashtag + exif serial + scan identity lifts) — with every edge carrying its provenance record id:
overcast doctor --json
overcast case init --json
overcast graph --no-open --json # build; inspect the payload's nodes/edges/hubs
overcast graph --json # (also opens the viewer) hand-rolled canvas, no CDN/egress
- Focus a node's 2-hop neighborhood — a target, a finding, a record id, a media
ref, or an entity's text. The anchor is never trimmed;
--limitdrops lowest-degree leaf entities first,--sinceis capture-time-aware (an in-window finding pulls its out-of-window source record back in):
overcast graph --focus <target-id> --json # everything around a line of investigation
overcast graph --focus "+15551234567" --json # everything touching an entity value
overcast graph --since 7d --limit 250 --json # recent, trimmed
- (Optional) Run the opt-in LLM entity/relation pass.
--extractsends evidence TEXT to your brain LLM (BYO, text-only), caches to.overcast/graph/extract.jsonl(delete the file to re-extract), and marks every result leads-not-proof (payload.caveat). It co-filters with--since:
overcast graph --extract --json # adds LLM-inferred entities/relations (cached)
overcast graph --extract --since 7d --focus <target-id> --json
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.
- 10d ago First seen · 82 lines · 60 tokens per session scan A f7896b3aff04
overcast-connect-the-dots is a skill published in the GitHub repository kdr/overcast (16 stars, last pushed 7d ago), licensed Apache-2.0. It adds 60 tokens to every session and 998 once invoked, about $0.0003 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 2026-08-30.
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