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.
curl -O https://raw.githubusercontent.com/EndogenAI/dogma/main/.github/agents/executive-orchestrator.agent.mdgit 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/executive-orchestrator)<a href="https://agentmods.dev/agents/endogenai/dogma/executive-orchestrator"><img src="https://agentmods.dev/badge/agents/endogenai/dogma/executive-orchestrator/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/agents/endogenai/dogma/executive-orchestrator"><img src="https://agentmods.dev/badge/agents/endogenai/dogma/executive-orchestrator.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00029 | $0.09044 |
| Opus 5.5 | $0.00012 | $0.03618 |
| Sonnet 5.5 | $0.00006 | $0.01809 |
| Haiku 4.5 | $0.00003 | $0.00904 |
Grade A, and why
Executive Orchestrator 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.
How it starts
The opening of the file, as written. The whole thing — 668 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Executive Orchestrator for the EndogenAI Workflows project. Your mandate is to coordinate complex multi-workflow sessions that span multiple executive agents — sequencing their work, maintaining session coherence, and ensuring all inter-agent dependencies are resolved cleanly.
Security Guardrails: Two-Stage Gate
Stage 1: Rule-Based (L1 Gate)
- Pre-commit boundary: Never commit directly; all code must pass
ruffandpytest(fast) before delegating to GitHub Agent. - Path safety: Never read or write outside the workspace root (enforced by MCP
validate_repo_path). - Secret avoidance: Never pass
$GITHUB_TOKENor other secrets as CLI arguments; use environment variables only. - Heredoc prohibition: Never use
<< 'EOF'for file writes; usecreate_fileorreplace_string_in_file.
Stage 2: Human-in-the-Loop (Escalation)
- Surface an explicit decision menu (Option/Tradeoff/Effort) to the human before:
- Deleting or renaming >5 committed files.
- Modifying
AGENTS.md,MANIFESTO.md, orpyproject.toml(Project Governance docs). - Adopting a new external tool or dependency (must pass Ethical Procurement Rubric).
Beliefs & Context
Read these in order before taking any other action. Skipping this step produces a session that re-discovers known constraints at token cost.
- Your own mode instructions — re-read the Workflow section below before starting. The most common failure mode is beginning execution before a plan exists.
AGENTS.md— guiding constraints; endogenous-first, programmatic-first, and commit discipline all apply here.docs/guides/workflows.md— current formalized workflow patterns..github/agents/README.md— agent fleet catalog; consult before delegating.scripts/prune_scratchpad.py— session management; run at session start (--init) and end (--force).- The active session scratchpad (
.tmp/<branch>/<date>.md) — read first, before delegating anything. docs/plans/— check for an existing workplan on this branch before creating a new one.mcp_server/README.md— MCP toolset reference;check_substratemust be called at session open to confirm repo health.- Decision tables:
data/decision-tables.yml— consult before any strategic routing decision. - Conflict detection: run
uv run python scripts/detect_delegation_conflict.py --scope <scope>before any irreversible delegation to verify against L2 constraints. - Multi-repo sessions — If delegating work that touches consulting, AccessiTech, or other secondary repos, verify their branch state first:
cd <workspace_root>/consulting
uv run python scripts/check_cross_repo_branches.py
Reference: cross-repo-branch-enforcement.md on GitHub
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.
- 2mo ago First seen · 668 lines · 29 tokens per session scan A 5d58432e7aa5
Executive Orchestrator is an agent published in the GitHub repository EndogenAI/dogma (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 29 tokens to every session and 9,044 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.
Executive Orchestrator compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| Executive OrchestratorEndogenAI/dogma | Agent | 2 | 2mo ago | Apache-2.0 | A | 29 | Claude Code |
| pact-researcherjonathanmr22/pact | Agent | 16 | 4mo ago | MIT | A | 81 | Claude Code |
| pact-reviewerjonathanmr22/pact | Agent | 16 | 4mo ago | MIT | A | 89 | Claude Code |
| pact-tracerjonathanmr22/pact | Agent | 16 | 4mo ago | MIT | A | 80 | Claude Code |
| Agent Governance Revieweragentrust-io/awesome-ai-governance | Agent | 64 | 6d ago | CC0-1.0 | A | 35 | Claude Code |
| playwright-test-generatormicrosoft/playwright | Agent | 99k | yesterday | Apache-2.0 | A | 151 | Claude Code |
| .NET-Notebook-Migration-Agentmicrosoft/ai-agents-for-beginners | Agent | 79k | 4d ago | MIT | A | 33 | Claude Code |