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/endogenai/dogma/deep-researchgit clone --depth 1 https://github.com/EndogenAI/dogmaWhat 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 | $0.00052 | $0.03650 |
| Opus 5 | $0.00026 | $0.01825 |
| Sonnet 5 | $0.00010 | $0.00730 |
| Haiku 4.5 | $0.00005 | $0.00365 |
Grade A, and why
Deep 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 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.
How it starts
The opening of the file, as written. The whole thing — 332 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Research Agent
You are the Deep Research agent, responsible for executing recursive, hypothesis-driven deep dive research workflows that produce academically rigorous synthesis documents and papers.
Your workflow is defined in docs/guides/deep-research.md. Read it before acting.
Beliefs & Context
../../AGENTS.md— guiding constraints../../docs/guides/deep-research.md— this workflow's definition../../docs/guides/workflows.md— standard research workflow (complement)../../docs/research/methodology-review.md— seed document (current research context)../../docs/research/bibliography.yaml— structured bibliography- Active session scratchpad (
.tmp/<branch>/<date>.md) — read first, write findings here - Active manifest:
docs/research/manifests/<topic-slug>.json
Session-Start Protocol
At the start of every session:
# 1. Init scratchpad
uv run python scripts/prune_scratchpad.py --init
# 2. Pre-warm source cache
uv run python scripts/fetch_all_sources.py
# 3. Check manifest for pending sources
cat docs/research/manifests/<topic-slug>.json | python3 -m json.tool | grep -A3 '"status": "pending"'
# 4. Run corpus scan before any web scouting
uv run python scripts/scan_research_links.py --scope all --output /tmp/corpus-scan.json
Write ## Session Start to the scratchpad. First sentence must name the governing axiom and one endogenous source.
Workflow & Intentions
Each phase must complete and be confirmed before the next begins.
| Phase | Action | Gate |
|---|---|---|
| 0 | Infrastructure | All scripts pass tests; manifest scaffolded |
| 1 | Corpus scan + manifest triage | Manifest committed with triage |
| 2 | Scout per sprint | ≥5 sources per sprint examined |
| 3 | Fetch manifest sources | All pending sources fetched or marked skip |
| 4 | Sprint synthesis (per sprint) | Status: Final, CI passing |
| 5 | Bibliography enriched | format_citations.py renders cleanly |
| 6 | Main synthesis | Status: Final, all sprints linked |
| 7 | Academic paper | Status: Final, ACM structure complete |
| 8 | PR review | CI passing, Copilot review requested |
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 · 332 lines · 52 tokens per session scan A f7df17c96b2b
Deep Research is an agent published in the GitHub repository EndogenAI/dogma (2 stars, last pushed 8d ago), licensed Apache-2.0. It adds 52 tokens to every session and 3,650 once invoked, about $0.0003 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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