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 resolve-ai-oss/resolve-ai-plugins --skill investigategit clone --depth 1 https://github.com/resolve-ai-oss/resolve-ai-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/skills/resolve-ai-oss/resolve-ai-plugins/investigate)<a href="https://agentmods.dev/skills/resolve-ai-oss/resolve-ai-plugins/investigate"><img src="https://agentmods.dev/badge/skills/resolve-ai-oss/resolve-ai-plugins/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/resolve-ai-oss/resolve-ai-plugins/investigate"><img src="https://agentmods.dev/badge/skills/resolve-ai-oss/resolve-ai-plugins/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 | $0.00081 | $0.00946 |
| Opus 5 | $0.00041 | $0.00473 |
| Sonnet 5 | $0.00016 | $0.00189 |
| Haiku 4.5 | $0.00008 | $0.00095 |
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 9d 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Investigate with Resolve
Opens an existing investigation, or starts a new one after first discovering whether Resolve is already working on the same thing. Starting a new investigation kicks off a real run — always confirm explicitly with the user before doing so.
Arguments
If $ARGUMENTS is non-empty, treat it as the input and route immediately (see below).
If $ARGUMENTS is empty, ask the user what they want to investigate (a URL, an ID, or a problem description). Treat their next reply as the input.
Routing
Path A — Input is a Resolve URL or canvas ID (URLs follow <your-resolve-host>/chat/<id>; the ID is the last path segment, or the user may give you just the ID directly).
- Extract the canvas ID.
- Call
get_investigation. - Summarize state for the user: status, phase, top theories, alerts. Include the canvas URL.
- Drill into specific theories, the report, or evidence via
read_filewhen the user asks.
No confirmation needed — this path is read-only.
Path B — Input is a free-form problem description (e.g. "frontend is slow", "DB queries timing out", an alert name).
Before starting fresh, always check whether Resolve is already working on this.
- Discover existing candidates first. If recent
list_alerts/list_investigationsoutput is already in the conversation (e.g. from a prioroverview,alerts, orinvestigationscall), reuse it — do not re-fetch. Otherwise call those tools for recent activity. Either way, match the returned items against the user's input locally (by title, alert rule, labels, and recency) to find anything Resolve is already working on. Read-only — costs nothing and prevents duplicating in-flight work. - If candidates exist, surface the top matches with their canvas URLs and ask the user: "Open one of these, or start a new investigation?" Wait for an explicit answer. If they pick one, switch to Path A on that ID. Otherwise fall through.
- Compose the investigation prompt. Resolve is starting from a blank slate — include grounded context generously. Better to over-include than under-include:
- File paths, services, components, or subsystems the user pointed at
- Error messages, log lines, stack traces, exception types (paste them verbatim)
- Symptoms: what's broken, who's affected, when it started, what changed recently
- Git context (branch, recent commits, working changes) when the issue may be tied to a local change
- URLs the user referenced (Slack threads, dashboards, alert pages, related canvases)
- Suspected causes, hypotheses, or ruled-out paths the user has already explored
- Reproduction steps, environment details, or scope (single user vs widespread)
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.
- 9d ago First seen · 58 lines · 81 tokens per session scan A 7f1104a22a01
investigate is a skill published in the GitHub repository resolve-ai-oss/resolve-ai-plugins (4 stars, last pushed yesterday), licensed Apache-2.0. It adds 81 tokens to every session and 946 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 2026-08-31.
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