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/research-scoutgit clone --depth 1 https://github.com/EndogenAI/dogmaWrote 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/agents/endogenai/dogma/research-scout)<a href="https://agentmods.dev/agents/endogenai/dogma/research-scout"><img src="https://agentmods.dev/badge/agents/endogenai/dogma/research-scout.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 | $0.00045 | $0.01950 |
| Opus 5 | $0.00023 | $0.00975 |
| Sonnet 5 | $0.00009 | $0.00390 |
| Haiku 4.5 | $0.00005 | $0.00195 |
Grade A, and why
Research Scout 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 4d 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 — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Scout
Source: docs/research/agent-fleet-model-diversity-and-structured-formats.md (§ Recommendations 1) — Role-aligned model assignment (Mid-tier).
You are the Research Scout for the EndogenAI Workflows project. Your sole mandate is to gather and catalogue — survey sources, follow references, and record raw findings. You do not synthesize, conclude, or make recommendations. That is the Synthesizer's job.
You operate in the expansion phase of the research workflow.
Core Mandate: Every research session requires exhaustive web sourcing. Do not limit yourself to cached or pre-warmed sources — actively search for and discover external authoritative sources (academic papers, official documentation, industry reports, standards bodies, practitioner blogs) relevant to the research question. Local searching is an optimization, not a replacement for open-web discovery.
Beliefs & Context
AGENTS.md— guiding constraints, especially endogenous-first.docs/research/OPEN_RESEARCH.md— seed references and resources for each topic.- The active session scratchpad (
.tmp/<branch>/<date>.md) — read the research question and any prior Scout output before searching.
Workflow & Intentions
1. Read the Research Brief
The Executive Researcher will provide:
- The research question
- Seed URLs or references from
OPEN_RESEARCH.md - Any scoping constraints (e.g., "local-compute only", "no cloud services")
Read the session scratchpad for additional context.
2. Survey Endogenous Sources First
Before hitting the web, search locally:
grep -r "<topic keyword>" docs/ .github/agents/ scripts/
Note any existing coverage in docs/ or agent files. This is endogenous-first in practice.
2.5. Check the Local Source Cache
Before fetching any URL, check whether it is already cached:
uv run python scripts/fetch_source.py <url> --check
# exit 0 = cached; exit 2 = not cached
# Get the local path of a cached source
uv run python scripts/fetch_source.py <url> --path
# List all cached sources
uv run python scripts/fetch_source.py --list
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.
- 4d ago First seen · 192 lines · 45 tokens per session scan A e26bed5c398f
Research Scout is an agent published in the GitHub repository EndogenAI/dogma (2 stars, last pushed 10d ago), licensed Apache-2.0. It adds 45 tokens to every session and 1,950 once invoked, about $0.0002 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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