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/asteasolutions/ai-toolkit/grounded-researchnpx skills add asteasolutions/ai-toolkit --skill grounded-researchgit clone --depth 1 https://github.com/asteasolutions/ai-toolkitWrote 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/asteasolutions/ai-toolkit/grounded-research)<a href="https://agentmods.dev/skills/asteasolutions/ai-toolkit/grounded-research"><img src="https://agentmods.dev/badge/skills/asteasolutions/ai-toolkit/grounded-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 | $0.00117 | $0.01724 |
| Opus 5 | $0.00059 | $0.00862 |
| Sonnet 5 | $0.00023 | $0.00345 |
| Haiku 4.5 | $0.00012 | $0.00172 |
Grade A, and why
grounded-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 6d 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 — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Grounded research
Leading word: audit
Run research as an audit: every conclusion must trace to exact evidence, survive a counter-case, and expose its weak spots. The goal is not maximal length; the goal is a source-backed answer the user can inspect.
Load a reference only when it applies:
references/web.md— evidence is on the web.references/codebase.md— evidence is in a repo or local files.
For hybrid tasks load both branch files and keep web receipts separate from local receipts.
Step 1: Classify the branch and depth
Choose both a branch and a depth before researching. State the assumption only when it affects interpretation.
Branches
- Evidence branch: what is true, likely true, safest, best supported, most reliable, or most accurate.
- Opinion branch: what people think, user sentiment, complaints, reviews, Reddit/X/forum reactions, or community experience.
- Product/tool branch: whether to adopt, compare, trust, buy, configure, or rely on a tool, model, library, service, API, device, or workflow.
- Policy/legal/medical/financial branch: current rules or high-stakes guidance. Use current primary sources and disclose jurisdiction or scope limits.
Depths
- Light audit: simple fact-check, single narrow claim, or low-stakes answer. Use at least one strong source; include countercheck only if obvious.
- Standard audit: default for research. Use primary sources when available, one or more independent corroborating sources, an adversarial check, and concise confidence labels.
Completion criterion: branch and depth are chosen, and the evidence plan matches the user’s stakes instead of forcing every answer into the heaviest format.
Step 2: Researcher pass
Build the strongest source-backed answer. A material claim is one that affects the answer's conclusion, confidence, recommendation, or interpretation.
- Among sources in the same tier, prefer ones that support exact passage links, especially text fragment links. Never pick a weaker source because it has a fragment link.
- Use current sources when facts may have changed.
- Capture only evidence that directly supports or weakens a material claim.
- Separate findings from interpretation and recommendation.
- Track non-fragment links, unavailable primary sources, old sources, missing jurisdictions, missing versions, and uncertainty.
What ships with it
3 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.
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.
- 6d ago First seen · 164 lines · 117 tokens per session scan A 9cea01bdbc85
grounded-research is a skill published in the GitHub repository asteasolutions/ai-toolkit (5 stars, last pushed 5d ago), licensed MIT. It adds 117 tokens to every session and 1,724 once invoked, about $0.0006 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 2026-08-31.
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