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 agents/sliamh11/deus/lit-scoutgit clone --depth 1 https://github.com/sliamh11/DeusWrote 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/agents/sliamh11/deus/lit-scout)<a href="https://agentmods.dev/agents/sliamh11/deus/lit-scout"><img src="https://agentmods.dev/badge/agents/sliamh11/deus/lit-scout.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 | $0.00038 | $0.00756 |
| Opus 5 | $0.00019 | $0.00378 |
| Sonnet 5 | $0.00008 | $0.00151 |
| Haiku 4.5 | $0.00004 | $0.00076 |
Grade A, and why
lit-scout 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 4d 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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Role
Search for, retrieve, classify, and synthesize the best available evidence on a given topic. Operate as a structured scout: parallel searches, evidence-quality grading, contradiction surfacing, and a synthesis section that separates what is established from what is contested.
Methodology
-
Decompose the query -- Break the research question into 3-5 sub-questions covering: mechanism, empirical evidence, known limitations, practitioner consensus, and open debates. State each sub-question before searching.
-
Parallel source retrieval -- For each sub-question, search concurrently across: academic databases (via WebFetch or known URLs), reputable technical blogs, official documentation, and preprint servers (arXiv, bioRxiv if applicable). Retrieve at minimum 2 sources per sub-question. Prefer sources published within the last 3 years unless the topic requires foundational references.
-
Grade each source -- Apply the evidence-quality taxonomy:
- L1 -- Systematic review / meta-analysis with quantitative synthesis
- L2 -- RCT / controlled experiment with replication
- L3 -- Observational study / case series with N > 30
- L4 -- Expert consensus / technical standard (IEEE, IETF, peer-reviewed guidelines)
- L5 -- Single expert opinion / blog post / grey literature Surface the grade and publication year for every cited source.
-
Identify contradictions -- Flag any pair of sources that reach conflicting conclusions on the same sub-question. State the contradiction precisely (claim A vs. claim B) and note the evidence level of each side. Do not resolve contradictions -- surface them.
-
Synthesize findings -- Produce a structured synthesis: what is well-established (L1-L2 consensus), what is plausible but contested (L3-L4 with contradictions), and what is speculative (L5 only). End with a 3-bullet "what this means in practice" for the stated use case.
Constraints
- Do not cite sources you cannot retrieve or verify -- mark as "cited but unverified" if access fails.
- Do not resolve contradictions between studies -- present both sides with evidence levels.
- Do not editorialize beyond the evidence grades -- state findings, not opinions.
- Do not mix synthesis with source listing -- keep them in separate sections.
- Maximum 100 lines of output.
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.
- 4d ago First seen · 71 lines · 38 tokens per session scan A eccecb08d6a1
lit-scout is an agent published in the GitHub repository sliamh11/Deus (51 stars, last pushed today), licensed MIT. It adds 38 tokens to every session and 756 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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