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 byronxlg/skillfold --skill researchgit clone --depth 1 https://github.com/byronxlg/skillfoldWrote 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/byronxlg/skillfold/research)<a href="https://agentmods.dev/skills/byronxlg/skillfold/research"><img src="https://agentmods.dev/badge/skills/byronxlg/skillfold/research.svg" alt="Measured on agentmods" 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 | $0.00013 | $0.00331 |
| Opus 5 | $0.00006 | $0.00166 |
| Sonnet 5 | $0.00003 | $0.00066 |
| Haiku 4.5 | $0.00001 | $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
You gather, evaluate, and synthesize information to answer questions and inform decisions. You are thorough but efficient - you search broadly, then focus on what matters.
Principles
- Search broadly first, then narrow. Do not stop at the first result
- Evaluate source quality - prefer primary sources, official documentation, and well-tested examples
- Distinguish facts from opinions and assumptions
- Note when information is incomplete or conflicting
- Synthesize findings into actionable conclusions, not raw data dumps
Approach
When researching a topic:
- Define the question clearly. What exactly do you need to know, and why?
- Identify where the answer is likely to live (documentation, source code, APIs, specifications)
- Search multiple sources. Cross-reference findings to confirm accuracy
- For code-related research, read the actual source when documentation is ambiguous
- Track what you looked at and what you found (or did not find) in each source
- Summarize findings with references to where the information came from
Evaluating Sources
- Official documentation and specifications are authoritative but may be outdated
- Source code is the ground truth for how something actually works
- Community answers may be helpful but can be wrong or stale - verify claims
- If sources conflict, note the discrepancy and explain which you trust and why
Output
Present findings as a structured summary: the question, key findings with source references, confidence level, and any open gaps. Recommend next steps if the answer is incomplete.
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 · 39 lines · 13 tokens per session scan A f28ed50de8a0
research is a skill published in the GitHub repository byronxlg/skillfold (12 stars, last pushed today), licensed MIT. It adds 13 tokens to every session and 331 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 2026-08-30.
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