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 skills/attckdigital/smith/smith-researchnpx skills add ATTCKDigital/smith --skill smith-researchgit clone --depth 1 https://github.com/ATTCKDigital/smithWhat 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 | $0.00095 | $0.02439 |
| Opus 5 | $0.00048 | $0.01220 |
| Sonnet 5 | $0.00019 | $0.00488 |
| Haiku 4.5 | $0.00010 | $0.00244 |
Grade A, and why
smith-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 3d 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 — 220 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Smith Research — Website & Company Deep Research
Produce an auditable research dossier on a target site + company. The design separates extraction (deterministic scripts, zero LLM) from interpretation (LLM subagents that see ONLY already-stored, cited chunks). The guarantee is traceability, not omniscience: every published sentence is citation-gated and adversarially entailment-checked, and a deterministic LLM-free gate fails the run rather than ship an uncited claim.
Arguments: $ARGUMENTS (first positional token is the target domain)
When to use
- You need a complete, source-backed picture of a company: what it is, what it offers, pricing, target audience, marketing angle, plus background — PR/news, funding, and leadership.
- You want the underlying corpus stored so you can ask follow-up questions later.
When NOT to use
- Quick one-off lookups (use a direct web search).
- Authenticated/paywalled content (out of scope).
Vault Logging
Throughout, log significant events to the vault session log. Read the path from
.smith/vault/.current-session. If missing or the vault is not initialized, skip
logging silently. Immediately before every Agent tool call, append a block naming
the phase, subagent_type, and model (the Agent return value does not expose
these to the parent, so this is the only capture point).
Prerequisites (checked in Phase 0)
- Docker running with a Qdrant container on :6333.
- Ollama running with
nomic-embed-textpulled. - The skill-owned venv + Playwright browser + Playwright WS server (Phase 0 bootstraps these).
Engine (deterministic CLI — no LLM)
All crawling/extraction/indexing/retrieval/verification bookkeeping is done by:
python3 skills/smith-research/scripts/run.py <subcommand> [flags]
Subcommands: check, discover, crawl, index, background, retrieve,
evidence-check, record-claim, verify-report, status. See
skills/smith-research/scripts/README.md and specs/32-smith-research/contracts/cli.md.
What ships with it
34 files 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.
- README.md 5.2 KB
- scripts/README.md 2.4 KB
- scripts/requirements.txt 608 B
- scripts/run.py 8.9 KB runs code
- scripts/smith_research/__init__.py 603 B runs code
- scripts/smith_research/bg_research.py 13 KB runs code
- scripts/smith_research/browser.py 3.8 KB runs code
- scripts/smith_research/checkpoint.py 3.6 KB runs code
- scripts/smith_research/chunker.py 2.9 KB runs code
- scripts/smith_research/classifier.py 2.4 KB runs code
- scripts/smith_research/config.py 3.9 KB runs code
- scripts/smith_research/crawler.py 7.0 KB runs code
- scripts/smith_research/discover.py 9.1 KB runs code
- scripts/smith_research/embedder.py 4.2 KB runs code
- scripts/smith_research/extractor.py 7.6 KB runs code
- scripts/smith_research/indexer.py 4.7 KB runs code
- scripts/smith_research/ledger.py 11 KB runs code
- scripts/smith_research/logger.py 2.9 KB runs code
- scripts/smith_research/models_research.py 2.9 KB runs code
- scripts/smith_research/models.py 1.4 KB runs code
- scripts/smith_research/prereqs.py 2.7 KB runs code
- scripts/smith_research/qdrant_store.py 5.8 KB runs code
- scripts/smith_research/reddit_search.py 2.6 KB runs code
- scripts/smith_research/reddit_url.py 7.1 KB runs code
- scripts/smith_research/retrieval.py 6.8 KB runs code
- scripts/smith_research/serp_scraper.py 6.6 KB runs code
- scripts/smith_research/verify_report.py 7.1 KB runs code
- scripts/smith_research/workspace.py 3.8 KB runs code
- scripts/start-playwright-server.sh 3.2 KB runs code
- scripts/tests/test_background.py 3.0 KB runs code
- scripts/tests/test_chunker.py 1.4 KB runs code
- scripts/tests/test_discover.py 1.6 KB runs code
- scripts/tests/test_ledger.py 2.8 KB runs code
- scripts/tests/test_verify_report.py 5.0 KB runs code
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.
- 3d ago First seen · 220 lines · 95 tokens per session scan A 6cddfc06fc9e
smith-research is a skill published in the GitHub repository ATTCKDigital/smith (52 stars, last pushed 1mo ago), licensed MIT. It adds 95 tokens to every session and 2,439 once invoked, about $0.0005 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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