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 jxoesneon/Ciel --skill researchgit clone --depth 1 https://github.com/jxoesneon/CielWrote 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/jxoesneon/ciel/research)<a href="https://agentmods.dev/skills/jxoesneon/ciel/research"><img src="https://agentmods.dev/badge/skills/jxoesneon/ciel/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/jxoesneon/ciel/research"><img src="https://agentmods.dev/badge/skills/jxoesneon/ciel/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 | $0.00015 | $0.00326 |
| Opus 5 | $0.00008 | $0.00163 |
| Sonnet 5 | $0.00003 | $0.00065 |
| Haiku 4.5 | $0.00002 | $0.00033 |
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 8d 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
Multi-source synthesis with citations.
Operations
research.deep(question, budget_tokens?)— iterative search + fetch + synthesize.research.compare(a, b)— side-by-side analysis.research.verify(claim, sources?)— evidence-based check.research.outline(topic)— structured outline to drive follow-up.
I/O Contract
io_contract:
input: { op, question, "budget_tokens?", "since?" }
output: { summary, citations: [ { url, excerpt, confidence } ], confidence }
idempotent: true (approximate)
side_effects: [network]
Principles
- Multi-source required; never trust a single page.
- Official docs > community > blog > forum.
- Citations stored in MemPalace for audit;
fetch_hashpreserved. - Returns an honest confidence estimate; below threshold triggers user escalation.
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.
- 8d ago First seen · 40 lines · 15 tokens per session scan A a7db64af9da7
research is a skill published in the GitHub repository jxoesneon/Ciel (1 stars, last pushed yesterday), licensed Apache-2.0. It adds 15 tokens to every session and 326 once invoked, about $0.0001 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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