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.
git clone --depth 1 https://github.com/ghaida/intentWrote 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/rules/ghaida/intent/investigate)<a href="https://agentmods.dev/rules/ghaida/intent/investigate"><img src="https://agentmods.dev/badge/rules/ghaida/intent/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/rules/ghaida/intent/investigate"><img src="https://agentmods.dev/badge/rules/ghaida/intent/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 | $0.06036 | $0.06036 |
| Opus 5.5 | $0.02414 | $0.02414 |
| Sonnet 5.5 | $0.01207 | $0.01207 |
| Haiku 4.5 | $0.00604 | $0.00604 |
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 1mo 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 — 418 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Investigate
Overview
Research is the foundation of intentional design. Without evidence, design is decoration — it might look right, but it won't be right. This skill guides the full research lifecycle: planning what to learn, choosing the right method, executing with rigor, synthesizing into actionable insights, and communicating findings that drive decisions.
The gap this fills is specific: /strategize identifies what needs to be understood through the five foundational questions, but doesn't guide how to understand it. /investigate owns that how. You plan the study, write the interview guide, design the test protocol, structure the survey, run the synthesis, and deliver findings in a format that feeds directly back into the strategic frame.
Research is not a phase you pass through once. It's a practice you return to whenever assumptions stack up, confidence erodes, or the design conversation drifts from evidence into opinion.
Skill family
/investigate connects to the full Intent skill system:
/strategize: Your primary partner. Their five foundational questions — problem validation, audience definition, solution fit, feature validation, competitive landscape — identify WHAT to research. You determine HOW. When research is complete, findings flow back to/strategizefor synthesis into the strategic frame./blueprint: Your findings about how users experience systems, services, and processes inform their architectural decisions. Share journey-based synthesis and contextual inquiry findings directly./journey: Usability test findings and contextual inquiry observations feed directly into flow design. Share task completion data, error patterns, and observed navigation behaviors./organize: Card sort and tree test results are direct inputs for information architecture. Share clustering patterns, mental models, and navigation expectations./articulate: Interview language, terminology patterns, and content comprehension findings inform content strategy. Share how users actually talk about the problem./evaluate: Your findings inform their assessment criteria. When/evaluateidentifies usability issues, you may be called back to investigate root causes through targeted research./measure: The quantitative complement to your qualitative work. Survey data and analytics review bridge the two skills. When their metrics reveal behavioral patterns, you investigate the why behind the numbers./philosopher: Enter when research findings surprise you, contradict team assumptions, or reveal that you've been asking the wrong questions. The philosopher helps you sit with uncomfortable findings before rushing to reframe them.
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.
- 1mo ago First seen · 418 lines · 6,036 tokens per session scan A 11e480043aef
investigate is a cursor rule published in the GitHub repository ghaida/intent (214 stars, last pushed 7d ago), licensed CC0-1.0. It adds 6,036 tokens to every session, about $0.0241 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 2026-08-30.
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