Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Borda/AI-Rignpx agentmods add skills/borda/ai-rig/researchWrote 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/borda/ai-rig/research)<a href="https://agentmods.dev/skills/borda/ai-rig/research"><img src="https://agentmods.dev/badge/skills/borda/ai-rig/research/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/borda/ai-rig/research"><img src="https://agentmods.dev/badge/skills/borda/ai-rig/research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00021 | $0.01427 |
| Opus 5.5 | $0.00008 | $0.00571 |
| Sonnet 5.5 | $0.00004 | $0.00285 |
| Haiku 4.5 | $0.00002 | $0.00143 |
Grade A, and why
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 — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Before asking, read User Questions. Waits, plan updates, and test runs follow Agent Waits, Plan Updates, and Sandboxed Test Runs.
Research
Task-size routing follows Proportional Execution; this skill's specialized lifecycle and acceptance checks remain authoritative.
Source-backed research for documentation, API migration, paper, or state-of-the-art questions.
Input Schema
{
"question": "required research question",
"mode": "docs|sota|paper|methodology|code-fidelity",
"constraints": [
"optional codebase, compute, version, or implementation constraints"
],
"done_when": "recommendations are source-backed with caveats and confidence"
}
Workflow
01: Create run directory
Run create_run.py --skill research per ../../shared/helper-cli-contract.md.
02: Define research question, mode, and constraints
Modes:
docs: current API/docs/migration answer.sota: method comparison and implementation recommendation.paper: single-paper analysis.methodology: experiment design, metric, guard, and ablation review.code-fidelity: compare paper/spec claims against implementation.
03: Gather sources
Write <run-directory>/sources.md:
| Source | Type | Date/version | Why reliable | Used for |
| --- | --- | --- | --- | --- |
Source rules:
- Prefer primary docs, papers, specs, release notes, code.
- Use current live sources for volatile docs, dependencies, APIs.
- Mark stale/unavailable source explicitly.
- Never cite secondary summaries for high-impact claims unless independently corroborated.
For sota, paper, methodology, or code-fidelity, read and apply ../../shared/specialist-orchestration.md only when independent expertise improves correctness; otherwise never load it. Write <run-directory>/specialist-research-plan.md with context packs for:
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.
- 6d ago Changed 2cdee03edb80
- 10d ago Changed · +2 lines f06d831cf4f7
- 12d ago Changed 7fefca6a15ed
- 14d ago Changed ed62592a8c51
- 23d ago Changed 062e29fb94bb
- 24d ago Changed 27ab52281f05
- 28d ago Changed 50bf403b4375
- 29d ago Changed · +2 lines 59b887b05fac
- 1mo ago Changed 1f9cf863ee97
- 1mo ago First seen · 138 lines · 21 tokens per session scan A 33134ba3c1e1
research is a skill published in the GitHub repository Borda/AI-Rig (28 stars, last pushed today), licensed Apache-2.0. It adds 21 tokens to every session and 1,427 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.
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Quick dashboard health and status overview — checks the Agent Monitor API (port 4820), reports session/agent/event counts from /api/stats, confirms WebSocket connectivity, reads the redacted hook status returned by /api/settings/info, and shows data freshness (last event timestamp). Use to verify the monitoring system…
dag-map
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regression-watch
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