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.
git clone --depth 1 https://github.com/btspoony/mstar-harnessWrote 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/btspoony/mstar-harness/architect)<a href="https://agentmods.dev/agents/btspoony/mstar-harness/architect"><img src="https://agentmods.dev/badge/agents/btspoony/mstar-harness/architect.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 5.1 | $0.00023 | $0.00258 |
| Opus 5 | $0.00012 | $0.00129 |
| Sonnet 5 | $0.00005 | $0.00052 |
| Haiku 4.5 | $0.00002 | $0.00026 |
Grade A, and why
architect 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 3d 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.
What it actually says
Morning Star Role Binding
You are architect. The complete role prompt is provided by the mstar-roles skill.
- Skill:
mstar-rolesskill - Role reference:
references/architect.mdin themstar-rolesskill - Role parameters:
role_id=architect,mode=subagent
Mandatory First Steps
This file is a routing shell — NOT your complete role prompt. Before any work, load in order:
skill→mstar-harness-core(state machine, gates, routing — global SSOT)skill→mstar-roles(role mapping & parameter table)Read→references/architect.mdlisted above
System reminders like "ALREADY LOADED" refer to prior sessions — you MUST load these for THIS session.
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.
- 3d ago Changed · -2 lines · -31 tokens per session 505b020d738d
- 7d ago First seen · 36 lines · 54 tokens per session scan A a51ec5d8025f
architect is an agent published in the GitHub repository btspoony/mstar-harness (58 stars, last pushed yesterday), licensed MIT. It adds 23 tokens to every session and 258 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.
Other agents, from other repositories
qa-agent
The orchestrator (/ship) passes a MODE flag and the corresponding feature root.
doc-gen-agent
The orchestrator (/ship) passes a MODE flag determining where to read inputs.
designer-agent
The orchestrator (/plan) passes a MODE flag determining where to read PNGs and write design-spec.md.
db-agent
The DB Agent scans the live database schema and produces a structured JSON snapshot that all subsequent agents use to understand the data model. It never modifies the database. Ever.
youtube-transcriber
Sub-agent that extracts transcripts and metadata from YouTube videos and playlists. Uses youtube-transcript-api for captions and yt-dlp for metadata. Returns structured markdown with metadata.
section_writer_agent
An agent that writes a complete academic paper draft from evidence cards and an outline. It covers sections such as the abstract, introduction, related work, method, evaluation, limitations, and conclusion.