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/ssdeanx/deep-research/geminigit clone --depth 1 https://github.com/ssdeanx/deep-researchWhat 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 | $0.00000 | $0.03148 |
| Opus 5 | $0.00000 | $0.01574 |
| Sonnet 5 | $0.00000 | $0.00630 |
| Haiku 4.5 | $0.00000 | $0.00315 |
Grade A, and why
GEMINI 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 2d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 2d ago First seen · 387 lines · 0 tokens per session scan A 6a8ad6434c3b
GEMINI is an agent published in the GitHub repository ssdeanx/deep-research (37 stars, last pushed 11mo ago), with no licence file. It costs nothing until one of its globs matches a file; then it loads 3,148 tokens. 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.
Other agents, from other repositories
hyperresearch-instruction-critic
Use this agent in Layer 5 of the hyperresearch deep research pipeline. Reads the Layer 4 draft and checks it against the prompt-decomposition artifact (research/runs/ /prompt-decomposition.json) produced in Layer 0. Emits findings when atomic items from the prompt are missing, under-covered, out-of-order, or delivered…
hyperresearch-depth-investigator
Use this agent in Layer 3 of the hyperresearch deep research pipeline. Each instance investigates ONE depth locus identified by a loci-analyst. The agent reads existing vault sources relevant to the locus, fetches new sources as needed (via the hyperresearch-fetcher subagent), and writes ONE interim report note…
hyperresearch-fetcher
Research fetcher with primary-source-chasing agency. Fetches assigned URLs, reads and summarizes content, extracts structured claims, then follows citation chains and references to discover and fetch primary sources the secondary sources cite. Needs solid comprehension and judgment. Spawn multiple in parallel for bulk…
hyperresearch-loci-analyst
Use this agent in Layer 2 of the hyperresearch deep research pipeline. Reads the width corpus (the sources fetched during the Layer 1 sweep) and identifies 1—8 "depth loci" — specific questions where deeper investigation would meaningfully improve the final report. Spawn 2 of these in parallel; the orchestrator…
hyperresearch-dialectic-critic
Use this agent in Layer 5 of the hyperresearch deep research pipeline. Reads the Layer 4 draft and returns a findings list of places where the draft ignores, hedges, or straw-mans counter-evidence. Adversarial reading is real reasoning. Spawn ONCE per draft, in parallel with depth-critic and width-critic.
hyperresearch-readability-recommender
Step 16 agent. Reads the polished final report and writes a JSON file of readability RECOMMENDATIONS (not edits) for the orchestrator to selectively apply. Each recommendation includes the existing text (anchor), the suggested replacement, severity, rationale, and category (merge-paragraphs / break-paragraph /…