eve is a filesystem-first framework for building durable AI agents, with agent instructions, tools, and configuration kept in ordinary project files. It is for developers creating agents that can be inspected, extended, and operated through a conventional codebase. The catalogue add-ons support working with eve agents and their workflows.
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 vercel/eve --skill investigategit clone --depth 1 https://github.com/vercel/eveWrote 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/vercel/eve/investigate)<a href="https://agentmods.dev/skills/vercel/eve/investigate"><img src="https://agentmods.dev/badge/skills/vercel/eve/investigate/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/vercel/eve/investigate"><img src="https://agentmods.dev/badge/skills/vercel/eve/investigate.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 | $0.00016 | $0.00289 |
| Opus 5.5 | $0.00006 | $0.00116 |
| Sonnet 5.5 | $0.00003 | $0.00058 |
| Haiku 4.5 | $0.00002 | $0.00029 |
Grade A, and why
investigate 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 22d 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
Investigate
Determine unambiguously what the report means from the system's perspective. First establish whether it is real and reproducible. If not, pause and report that result.
Start at the observed effect and identify the code paths directly responsible. Climb one layer at a time across call frames, processes, network hops, and persistence boundaries. Go only as wide and deep as the evidence requires.
Keep an explicit hypothesis at every branch and try to disprove it. Prefer the simplest explanation that accounts for all observed evidence. Do not jump to solutions before diagnosis.
Standards
- Resolve every cited call frame and reference.
- Distinguish observations, inferences, and unknowns.
- Map relevant dependencies and identify other reports or users affected by the same mechanism.
- Question assumptions about timing, state, identity, retries, and execution boundaries.
- Stop when required evidence is unavailable rather than filling gaps with guesses.
Questions for every hypothesis
- How can this be disproved?
- Is there a simpler or more likely explanation?
- Which source references remain unresolved?
- Do the surrounding code and runtime state support the conclusion?
- Does this explain both why the behavior occurs and why it began now?
Return compact but complete evidence, the diagnosed mechanism, a decision tree when useful, and the smallest prognosis justified by the evidence.
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.
- 22d ago First seen · 31 lines · 16 tokens per session scan A 7735f2b00034
investigate is a skill published in the GitHub repository vercel/eve (5,573 stars, last pushed today), licensed Apache-2.0. It adds 16 tokens to every session and 289 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 2026-09-24.
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