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 agentmods add skills/stevesolun/ctx/researchnpx skills add stevesolun/ctx --skill researchgit clone --depth 1 https://github.com/stevesolun/ctxWhat 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 | $0.00038 | $0.00173 |
| Opus 5 | $0.00019 | $0.00086 |
| Sonnet 5 | $0.00008 | $0.00035 |
| Haiku 4.5 | $0.00004 | $0.00017 |
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 3d 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
Research
Clarify the decision or question the research must support. Prefer official documentation, source code, specifications, papers, and first-party APIs. Trace material claims to the source that owns them, distinguish source facts from inference, and account for publication and event dates when recency matters.
Use parallel research lanes only when the question has independent source areas and the coordination cost is worthwhile. Keep narrow lookups local.
Return findings in the form the user requested, with citations close to the claims they support. Create a repository artifact only when requested or when it clearly serves the task and is within the authorized scope.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 20 lines · 38 tokens per session scan A 4d27e5df2836
research is a skill published in the GitHub repository stevesolun/ctx (581 stars, last pushed 9d ago), licensed MIT. It adds 38 tokens to every session and 173 once invoked, about $0.0002 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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