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 ttxttx1111/sts2-llm --skill sts2-research-strategygit clone --depth 1 https://github.com/ttxttx1111/sts2-llmWrote 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/ttxttx1111/sts2-llm/sts2-research-strategy)<a href="https://agentmods.dev/skills/ttxttx1111/sts2-llm/sts2-research-strategy"><img src="https://agentmods.dev/badge/skills/ttxttx1111/sts2-llm/sts2-research-strategy/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/ttxttx1111/sts2-llm/sts2-research-strategy"><img src="https://agentmods.dev/badge/skills/ttxttx1111/sts2-llm/sts2-research-strategy.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 | $0.00043 | $0.00393 |
| Opus 5 | $0.00022 | $0.00197 |
| Sonnet 5 | $0.00009 | $0.00079 |
| Haiku 4.5 | $0.00004 | $0.00039 |
Grade A, and why
sts2-research-strategy 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 10d 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
STS2 strategy research workflow
Use this skill when the task is to resolve strategic uncertainty with outside evidence.
What this skill owns
- web research for matchup, archetype, route, reward, or economy questions
- comparing multiple sources instead of copying the first one
- translating general advice into the actual run state
- surfacing notes that are worth preserving in future reviews
Research loop
-
Define the narrow question
- examples: "Is this Ironclad Act 1 deck strong enough for an early elite?" or "How should Brand change early reward priorities?"
-
Gather evidence from more than one source
- prefer guides, discussion threads, or analyses that explain the tradeoffs
- avoid treating one flashy line as authoritative
-
Reconcile the advice with the run in front of you
- deck
- relics
- HP
- gold
- map
- potions
-
Return a decision-oriented answer
- say what the best line is now
- say what assumption would make that line wrong
-
Preserve anything durable
- if the finding is temporary, put it into the current playbook at ../../sts2-memory/current-playbook.md
- if it generalizes, hand it off to
sts2-review-runso it can be written into ../../sts2-memory/lesson-ledger.md
Constraints
- Do not paste generic advice without adaptation
- Prefer evidence-backed heuristics over one-off anecdotes
- Keep the output concise and actionable
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.
- 10d ago First seen · 47 lines · 43 tokens per session scan A 2e10d0ca7f9a
sts2-research-strategy is a skill published in the GitHub repository ttxttx1111/sts2-llm (41 stars, last pushed 1mo ago), licensed MIT. It adds 43 tokens to every session and 393 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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