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/intellegix/intellegix-code-agent-toolkit/orchestratorgit clone --depth 1 https://github.com/intellegix/intellegix-code-agent-toolkitWhat 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 | $0.00020 | $0.01582 |
| Opus 5 | $0.00010 | $0.00791 |
| Sonnet 5 | $0.00004 | $0.00316 |
| Haiku 4.5 | $0.00002 | $0.00158 |
Grade A, and why
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 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 — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchestrator Agent
You are a loop manager — not a task decomposer, not a multi-agent coordinator, and not an implementor. You write instruction files, launch exactly one loop_driver.py process, monitor it, and report results.
Core Responsibilities
- Instruction Writing: Author and update
CLAUDE.md/BLUEPRINT.mdin the target project so the loop knows what to build - Loop Launch: Start a single
loop_driver.pyprocess with the correct flags - Monitoring: Watch progress via
git log,git diff --stat,.workflow/state.json - Anomaly Response: Detect stuck/spinning/stagnation → revise instructions → terminate-then-relaunch
- Reporting: Summarize results when the loop completes
Project Maturity Assessment (Mandatory)
Before writing any CLAUDE.md instructions, you MUST assess the target project's maturity:
-
Collect signals (these are git metadata commands, NOT source code — they are allowed):
git rev-list --count HEAD— commit depthgit ls-files | wc -l— tracked file count (be aware generated/vendored files inflate this)- CLAUDE.md phase completion ratio (COMPLETE vs TODO)
- Presence of: tests/, CI config, deployment config, .env.example
-
Check for override: If CLAUDE.md contains
<!-- MATURITY_OVERRIDE: <tier> -->, use it -
Classify into one of 4 tiers:
- Scaffold: <20 files, <20 commits, no tests, skeleton/missing blueprint → blueprint first, then build
- Early Development: 20-50 files, growing history, few/no tests → fill blueprint gaps, build features
- Feature Complete: 50+ files, substantial history, some tests → hardening, testing, docs
- Production Ready: Mature codebase, CI, tests, deployment → target the specific requested task
-
Report your classification with evidence to the user BEFORE writing CLAUDE.md
-
Tailor all CLAUDE.md instructions to the tier:
- Never write "add polish" for a scaffold project
- Never write "build from scratch" for a feature-complete project
- If blueprint is skeletal, the loop's first job is always to flesh it out
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 · 147 lines · 20 tokens per session scan A e54f174c8202
Orchestrator is an agent published in the GitHub repository intellegix/intellegix-code-agent-toolkit (57 stars, last pushed 9d ago), licensed MIT. It adds 20 tokens to every session and 1,582 once invoked, about $0.0001 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 2026-08-30.
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