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 drujensen/aiagent --skill researchgit clone --depth 1 https://github.com/drujensen/aiagentWrote 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/drujensen/aiagent/research)<a href="https://agentmods.dev/skills/drujensen/aiagent/research"><img src="https://agentmods.dev/badge/skills/drujensen/aiagent/research/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/drujensen/aiagent/research"><img src="https://agentmods.dev/badge/skills/drujensen/aiagent/research.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 | $0.00042 | $0.00468 |
| Opus 5.5 | $0.00017 | $0.00187 |
| Sonnet 5.5 | $0.00008 | $0.00094 |
| Haiku 4.5 | $0.00004 | $0.00047 |
Grade A, and why
research 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 4d 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 — 30 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research
You have been activated to research a problem or feature request before any design or implementation work begins. Your job is to build an accurate, evidence-based picture of the current state - not to propose a solution and not to write code.
Instructions
- Restate the request in your own words in one or two sentences, so downstream steps can confirm you understood it correctly.
- Locate the relevant code. Use Read, Grep, and Glob to find the files, packages, and existing patterns that this request touches. Cite specific file paths and line numbers for every claim you make - do not describe code you have not actually read.
- Identify existing patterns to follow. This is a Go project using Domain-Driven Design with a strict separation between
internal/domain/(business logic, no external imports) andinternal/impl/(external integrations). Note which existing entities, services, repositories, or tools are analogous to what's being asked for. - Surface constraints and risks. Note anything that could make this harder than it looks: concurrency hazards, existing tests that encode assumptions, storage-format implications (JSON file repositories and MongoDB repositories must both stay consistent), or backward-compatibility concerns.
- List open questions. If something is genuinely ambiguous and you cannot resolve it by reading the code, say so explicitly rather than guessing.
Output
Produce a findings summary with these sections:
- Request - the one/two-sentence restatement
- Relevant files - a table of file paths with a one-line description of why each is relevant
- Existing patterns - what precedent already exists in the codebase for this kind of change
- Constraints and risks - anything that could complicate implementation
- Open questions - anything unresolved that the design phase needs to address
Do not propose a solution here. Do not write or edit any code. Your output is the input to the design phase, not a substitute for it.
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.
- 4d ago First seen · 30 lines · 42 tokens per session scan A 4c5b89147469
research is a skill published in the GitHub repository drujensen/aiagent (5 stars, last pushed 2mo ago), licensed MIT. It adds 42 tokens to every session and 468 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 2026-10-03.
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