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 TheStack-ai/swing-skills --skill swing-researchgit clone --depth 1 https://github.com/TheStack-ai/swing-skillsWrote 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/thestack-ai/swing-skills/swing-research)<a href="https://agentmods.dev/skills/thestack-ai/swing-skills/swing-research"><img src="https://agentmods.dev/badge/skills/thestack-ai/swing-skills/swing-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 | $0.00075 | $0.03435 |
| Opus 5 | $0.00037 | $0.01717 |
| Sonnet 5 | $0.00015 | $0.00687 |
| Haiku 4.5 | $0.00007 | $0.00344 |
Grade A, and why
swing-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 7d 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 — 278 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cross-Verified Research
Systematic research engine with anti-hallucination safeguards and source quality tiering.
Rules (Absolute)
- Never fabricate sources. No fake URLs, no invented papers, no hallucinated statistics.
- Source-traceability gate. Every factual claim must be traceable to a specific, citable source. If a claim cannot be traced to any source, mark it as Unverified (internal knowledge only) and state what verification would be needed. Never present untraced claims as findings.
- No speculation as fact. Do not present unverified claims using hedging language as if they were findings. Banned patterns: "아마도", "~인 것 같습니다", "~로 보입니다", "~수도 있습니다", "probably", "I think", "seems like", "appears to be", "likely". If a claim is not verified, label it explicitly as Unverified or Contested — do not soften it with hedging.
- BLUF output. Lead with conclusion, follow with evidence. Never bury the answer.
- Scaled effort. Match research depth to question scope:
- Narrow factual (single claim, date, specification): 2-3 queries, 2+ sources
- Technology comparison (A vs B): 5+ queries, 5+ sources
- Broad landscape (market analysis, state-of-art): 8+ queries, 8+ sources Default to the higher tier when scope is ambiguous.
- Cross-verify. Every key claim must appear in 2+ independent sources before presenting as fact. "Independent" means the sources conducted their own analysis or reporting — two articles that both cite the same original source (press release, blog post, study) count as ONE source, not two. Trace claims back to their origin.
- Scope before search. If the research question is ambiguous or overly broad, decompose it into specific sub-questions in Stage 1 and present them to the user for confirmation before proceeding to Stage 2. Do not research a vague question — sharpen it first.
Pipeline
Execute these 4 stages sequentially. Do NOT skip stages.
Stage 1: Deconstruct
Break the research question into atomic sub-questions.
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.
- 7d ago First seen · 278 lines · 75 tokens per session scan A 148b66c9c6cf
swing-research is a skill published in the GitHub repository TheStack-ai/swing-skills (40 stars, last pushed 4mo ago), licensed MIT. It adds 75 tokens to every session and 3,435 once invoked, about $0.0004 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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