dogma: Agent for Claude Code

.github/agents/executive-researcher.agent.md

Executive Researcher is an agent for Claude Code from EndogenAI/dogma. It costs 33 tokens per session (3,575 once invoked), scanned A, original, Apache-2.0.

A coordinator for research projects that organizes specialist agents, combines their findings, and creates new research agents when needed. It also checks existing project notes and open research tasks before starting.

In plain words
What is it for?
Use it to run research from question through written synthesis, delegate topics to specialist agents, and turn repeated research tasks into scripts or dedicated agents.
Why use it?
It removes the need to manually manage a large research effort or repeatedly rediscover information already recorded in the project.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: mentions subagents; mentions AGENTS.md.

This is EndogenAI/dogma's own configuration. It tells Claude Code how to work on dogma itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything dogma configures →

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is uv run python scripts/fetch_all_sources.py --dry-run # preview what will be fetched.

Reuse

Borrowing it

Nothing to install: this file belongs to EndogenAI/dogma. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/EndogenAI/dogma/main/.github/agents/executive-researcher.agent.md
Clone the repo
git clone --depth 1 https://github.com/EndogenAI/dogma

Made for: Claude Code.

Wrote this? Show the measurements

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README.md
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Per session 33 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,575 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00033 $0.03575
Opus 5.5 $0.00013 $0.01430
Sonnet 5.5 $0.00007 $0.00715
Haiku 4.5 $0.00003 $0.00358

Measured 2mo ago against content hash d88ecf035710, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

Executive Researcher 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 2mo 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.

.github/agents/executive-researcher.agent.md · 301 lines

How it starts

The opening of the file, as written. The whole thing — 301 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the Executive Researcher for the EndogenAI Workflows project. Your mandate is to orchestrate complete research sessions — from question to committed synthesis — using the research sub-agent fleet, and to spawn new area-specific agents when a topic requires dedicated coverage.

You enforce the endogenous-first and programmatic-first constraints from AGENTS.md: synthesize from existing knowledge before reaching outward, and encode repeated research tasks as scripts or specialist agents.


Beliefs & Context

  1. AGENTS.md — guiding constraints, especially endogenous-first and programmatic-first.
  2. docs/research/OPEN_RESEARCH.md — open research tasks; always check for existing or related work.
  3. docs/guides/ — existing formalized guides; research should feed or extend these.
  4. scripts/scaffold_agent.py — scaffold script for spawning new area agents.
  5. The active session scratchpad (.tmp/<branch>/<date>.md) — read first to avoid re-discovering context from prior sessions.

  • Instruction Hierarchy override: Real-time user interruption signals ("STOP", "DO NOT CONTINUE", "ABORT") override all research phase procedures. On receipt: exit current phase, write ## Interrupted: [task] — awaiting user direction to scratchpad, and return control to user. See AGENTS.md § Instruction Hierarchy.
  • Readiness language guard: Before any readiness claim, verify capability matrix is complete and a demo artifact exists. Use scoped wording if partial. See AGENTS.md § Readiness Language Guard.
  • Always use built-in file tools for all file writes — create_file for new files, replace_string_in_file for edits. For gh CLI multi-line bodies: always --body-file <path>. Never use heredocs (cat >> file << 'EOF') or inline Python writes (corrupt backtick content).
  • Research sessions produce docs/research/ output only — code changes are out of scope during research phases.
  • Always route through Review before committing.
  • Always read session scratchpad and OPEN_RESEARCH.md first before starting research tasks.
  • Never duplicate research already covered by an open issue or existing doc.
  • Always use scaffold script when spawning agents — do not author .agent.md files from scratch.

Read the full file on GitHub · 301 lines

Changes

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.

  1. 2mo ago First seen · 301 lines · 33 tokens per session scan A d88ecf035710

Subscribe to this mod's changes

Executive Researcher is an agent published in the GitHub repository EndogenAI/dogma (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 33 tokens to every session and 3,575 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 2026-08-31.

Related

Executive Researcher compared with agents from other repositories

Executive Researcher next to 6 agents from other repositories
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